Herr Prof. Dr.-Ing.

Frank Allgöwer

Institutsleiter
Institut für Systemtheorie und Regelungstechnik

Kontakt

+49 711 685-67733
+49 711 685-67735

Pfaffenwaldring 9
70569 Stuttgart
Deutschland
Raum: 2.246

Sprechstunde

Montag, 13:00 - 14:00 Uhr und nach Vereinbarung

  1. article

    1. F. Allgöwer et al., “Position paper on the challenges posed by modern applications to cyber-physical systems theory,” Nonlinear Analysis: Hybrid Systems, vol. 34, pp. 147–165, 2019.
    2. A. Romer, J. Berberich, J. Köhler, and F. Allgöwer, “One-shot verification of dissipativity properties from input-output data,” IEEE Control Systems Letters, vol. 3, pp. 709--714, 2019.
    3. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Event-triggered and self-triggered control for linear systems based on reachable sets,” Automatica, vol. 101, pp. 15–26, 2019.
    4. S. Wildhagen, M. A. Müller, and F. Allgöwer, “Predictive Control over a Dynamical Token Bucket Network,” IEEE Control Systems Letters, vol. 3, no. 4, pp. 21–26, 2019.
    5. S. Linsenmayer, D. V. Dimarogonas, and F. Allgöwer, “Periodic event-triggered control for networked control systems based on non-monotonic Lyapunov functions,” Automatica, vol. 106, pp. 35–46, 2019.
    6. J. Köhler, M. A. Müller, and F. Allgöwer, “Nonlinear reference tracking: An economic model predictive control  perspective,” IEEE Trans. Automat. Control, 2018.
    7. S. Linsenmayer, H. Ishii, and F. Allgöwer, “Containability with event-based sampling for scalar systems with time-varying delay and uncertainty,” IEEE Control Systems Letters, vol. 2, no. 4, pp. 725–730, 2018.
    8. S. Linsenmayer, D. V. Dimarogonas, and F. Allgöwer, “Event-Based Vehicle Coordination Using Nonlinear Unidirectional Controllers,” IEEE Trans.\ Control of Network Systems, vol. 5, no. 4, pp. 1575–1584, 2018.
    9. F. A. Lincoln et al., “Sensitization of glioblastoma cells to TRAIL- induced apoptosis by IAP- and Bcl-2 antagonism,” Cell Death and Disease, vol. 9, no. 1112, 2018.
    10. K. Kuritz, S. Zeng, and F. Allgöwer, “Ensemble Controllability of Cellular Oscillators,” IEEE Control Systems Letters, vol. 3, no. 2, pp. 296–301, 2018.
    11. D. Imig, K. Kuritz, N. Pollak, M. Rehm, and F. Allgöwer, “Death patterns resulting from cell cycle-independent cell death,” IFAC-PapersOnLine, vol. 51, no. 19, pp. 90–93, 2018.
    12. F. D. Brunner, M. A. Müller, and F. Allgöwer, “Enhancing Output-feedback MPC with Set-valued Moving Horizon Estimation,” IEEE Transactions on Automatic Control, vol. 63, no. 9, pp. 2976–2986, 2018.
    13. L. Danish, D. Imig, F. Allgöwer, P. Scheurich, and N. Pollak, “Bcl-2-mediated control of TRAIL-induced apoptotic response in the non-small lung cancer cell line NCI-H460 is effective at late caspase processing steps,” PLoS One, vol. 13, no. 6, 2018.
    14. K. Kuritz, D. Imig, M. Dyck, and F. Allgöwer, “Ensemble control for cell cycle synchronization of heterogeneous cell populations,” IFAC-PapersOnLine, vol. 51, no. 19, pp. 44–47, 2018.
    15. J. Berberich, J. Köhler, F. Allgöwer, and M. A. Müller, “Indefinite Linear Quadratic Optimal Control: Strict Dissipativity and Turnpike Properties,” IEEE Control Systems Letters, vol. 2, no. 3, pp. 399–404, 2018.
    16. K. Kuritz, D. Stöhr, N. Pollak, and F. Allgöwer, “On the relationship between cell cycle analysis with ergodic principles  and age-structured cell population models,” J. Theor. Biol., vol. 414, pp. 91–102, 2017.
    17. M. A. Müller and F. Allgöwer, “Economic and distributed model predictive control: recent developments  in optimization-based control,” SICE Journal of Control, Measurement, and System Integration, vol. 10, no. 2, pp. 39–52, 2017.
    18. J. M. Montenbruck, M. Arcak, and F. Allgöwer, “An Input-Output Framework for Submanifold Stabilization,” IEEE Trans. Automat. Control, vol. 62, no. 10, pp. 5170--5184, 2017.
    19. W. Halter, J. M. Montenbruck, Z. A. Tuza, and F. Allgöwer, “A resource dependent protein synthesis model for evaluating synthetic  circuits,” J. Theor. Biol., vol. 420, pp. 267–278, 2017.
    20. J. M. Montenbruck, D. Zelazo, and F. Allgöwer, “Fekete Points, Formation Control, and the Balancing Problem,” IEEE Trans. Automat. Control, vol. 62, no. 10, pp. 5069--5081, 2017.
    21. D. Schittler, T. Jouini, F. Allgöwer, and S. Waldherr, “Multistability equivalence between gene regulatory networks of different  dimensionality with application to a differentiation network,” Int. J. Robust and Nonlinear Control, 2016.
    22. K. D. Listmann, P. Wenzelburger, and F. Allgöwer, “Industrie 4.0 - (R)evolution ohne Regelungstechnik?,” at-Automatisierungstechnik, vol. 64, no. 7, pp. 507–520, 2016.
    23. J. M. Montenbruck and F. Allgöwer, “Asymptotic Stabilization of Submanifolds Embedded in Riemannian  Manifolds,” Automatica, vol. 74, pp. 349--359, 2016.
    24. F. D. Brunner, M. Heemels, and F. Allgöwer, “Robust self-triggered MPC for constrained linear systems: A tube-based  approach,” Automatica, vol. 72, pp. 73--83, 2016.
    25. S. Zeng, S. Waldherr, C. Ebenbauer, and F. Allgöwer, “Ensemble Observability of Linear Systems,” IEEE Trans. Automat. Control, vol. 61, no. 6, pp. 1452–1465, 2016.
    26. K. D. Listmann, P. Wenzelburger, and F. Allgöwer, “Industrie 4.0 - (R)evolution without Control Technologies?,” J. of The Society of Instrument and Control Engineers, vol. 55, no. 7, pp. 555–565, 2016.
    27. F. A. Bayer, M. Lorenzen, M. A. Müller, and F. Allgöwer, “Robust Economic Model Predictive Control using Stochastic Information,” Automatica, vol. 74, pp. 151–161, 2016.
    28. J. M. Montenbruck, M. Bürger, and F. Allgöwer, “Compensating Drift Vector Fields with Gradient Vector Fields for  Asymptotic Submanifold Stabilization,” IEEE Trans. Automat. Control, vol. 61, no. 2, pp. 388–399, 2016.
    29. S. Zeng, S. Waldherr, C. Ebenbauer, and F. Allgöwer, “Ensemble Observability of Linear Systems,” IEEE Trans.\ Automat.\ Control, 2016.
    30. J. M. Montenbruck, G. S. Schmidt, G. S. Seyboth, and F. Allgöwer, “On the Necessity of Diffusive Couplings in Linear Synchronization  Problems with Quadratic Cost,” IEEE Trans. Automat. Control, vol. 60, no. 11, pp. 3029–3034, 2015.
    31. G. Seyboth, D. V. Dimarogonas, K. H. Johansson, P. Frasca, and F. Allgöwer, “On Robust Synchronization of Heterogeneous Linear Multi-Agent Systems  with Static Couplings,” Automatica, vol. 53, pp. 392–399, 2015.
    32. M. A. Müller, D. Liberzon, and F. Allgöwer, “Norm-controllability of nonlinear systems,” IEEE Trans. Automat. Control, vol. 60, no. 7, pp. 1825–1840, 2015.
    33. D. Imig, N. Pollak, T. Strecker, P. Scheurich, F. Allgöwer, and S. Waldherr, “An individual-based simulation framework for dynamic, heterogeneous  cell populations during extrinsic stimulations,” J. Coupled Syst. Multiscale Dyn., vol. 3, no. 2, pp. 143–155, 2015.
    34. J. M. Montenbruck, M. Bürger, and F. Allgöwer, “Practical Synchronization with Diffusive Couplings,” Automatica, vol. 53, pp. 235–243, 2015.
    35. M. A. Müller, D. Angeli, and F. Allgöwer, “On necessity and robustness of dissipativity in economic model predictive  control,” IEEE Trans. Automat. Control, vol. 60, no. 6, pp. 1671–1676, 2015.
    36. J. M. Montenbruck, M. Bürger, and F. Allgöwer, “Synchronization of Diffusively Coupled Systems on Compact Riemannian  Manifolds in the Presence of Drift,” Syst. Contr. Lett., vol. 76, pp. 19–27, 2015.
    37. F. D. Brunner, M. Lazar, and F. Allgöwer, “Stabilizing model predictive control: On the enlargement of the terminal  set,” Int. J. Robust and Nonlinear Control, vol. 25, no. 15, pp. 2646–2670, 2015.
    38. G. Seyboth, D. V. Dimarogonas, K. H. Johansson, P. Frasca, and F. Allgöwer, “On Robust Synchronization of Heterogeneous Linear Multi-Agent Systems with Static Couplings,” Automatica, vol. 53, pp. 392–399, 2015.
    39. J. M. Montenbruck, M. Bürger, and F. Allgöwer, “Practical Synchronization with Diffusive Couplings,” Automatica, vol. 53, pp. 235–243, 2015.
    40. M. A. Müller, D. Angeli, and F. Allgöwer, “On necessity and robustness of dissipativity in economic model predictive control,” IEEE Trans.\ Automat.\ Control, vol. 60, no. 6, pp. 1671–1676, 2015.
    41. S. Schuler, U. Münz, and F. Allgöwer, “Decentralized state feedback control for interconnected systems with  application to power systems,” J. Proc. Contr., vol. 24, no. 2, pp. 379–388, 2014.
    42. K. Worthmann, M. Reble, L. Grüne, and F. Allgöwer, “The Role of Sampling for Stability and Performance in Unconstrained  Nonlinear Model Predictive Control,” SIAM J. Control Optim., vol. 52, no. 1, pp. 581–605, 2014.
    43. D. Schittler, T. Jouini, F. Allgöwer, and S. Waldherr, “Multistability equivalence between gene regulatory networks of different dimensionality with application to a differentiation network,” Int.\ J.\ Robust and Nonlinear Control, 2014.
    44. M. A. Müller, D. Angeli, and F. Allgöwer, “On the performance of economic model predictive control with self-tuning  terminal cost,” J. Proc. Contr., vol. 24, no. 8, pp. 1179–1186, 2014.
    45. G. Seyboth, J. Wu, J. Qin, C. Yu, and F. Allgöwer, “Collective Circular Motion of Unicycle Type Vehicles with Nonidentical  Constant Velocities,” IEEE Trans. Control of Network Systems, vol. 1, no. 2, pp. 167–176, 2014.
    46. S. Yu, M. Reble, H. Chen, and F. Allgöwer, “Inherent robustness properties of quasi-infinite horizon nonlinear  model predictive control,” Automatica, vol. 50, no. 9, pp. 2269–2280, 2014.
    47. M. Bürger, C. De Persis, and F. Allgöwer, “Dynamic Pricing Control for Constrained Distribution Networks with  Storage,” IEEE Trans. Control of Network Systems, vol. 2, no. 1, pp. 88–97, 2014.
    48. F. Bayer, M. A. Müller, and F. Allgöwer, “Tube-based Robust Economic Model Predictive Control,” J. Proc. Contr., vol. 24, no. 8, pp. 1237–1246, 2014.
    49. M. Löhning, M. Reble, J. Hasenauer, S. Yu, and F. Allgöwer, “Model predictive control using reduced order models: Guaranteed stability  for constrained linear systems,” J. Proc. Contr., vol. 24, no. 11, pp. 1647–1659, 2014.
    50. M. Ma, H. Chen, X. Liu, and F. Allgöwer, “Distributed model predictive load frequency control of multi-area  interconnected power system,” Int. J. Electrical Power & Energy Systems, vol. 62, pp. 289–298, 2014.
    51. M. Bürger, G. Notarstefano, and F. Allgöwer, “A Polyhedral Approximation Framework for Convex and Robust Distributed  Optimization,” IEEE Transactions on Automatic Control, vol. 59, no. 2, pp. 384–395, 2014.
    52. M. A. Müller, D. Angeli, and F. Allgöwer, “Transient average constraints in economic model predictive control,” Automatica, vol. 50, no. 11, pp. 2943–2950, 2014.
    53. M. A. Müller, D. Angeli, F. Allgöwer, R. Amrit, and J. B. Rawlings, “Convergence in economic model predictive control with average constraints,” Automatica, vol. 50, no. 12, pp. 3100–3111, 2014.
    54. S. Schuler, U. Münz, and F. Allgöwer, “Decentralized state feedback control for interconnected systems with application to power systems,” J.\ Proc.\ Contr., vol. 24, no. 2, pp. 379–388, 2014.
    55. K. Worthmann, M. Reble, L. Grüne, and F. Allgöwer, “The Role of Sampling for Stability and Performance in Unconstrained Nonlinear Model Predictive Control,” SIAM J.\ Control Optim., vol. 52, no. 1, pp. 581–605, 2014.
    56. S. Yu, M. Reble, H. Chen, and F. Allgöwer, “Inherent robustness properties of quasi-infinite horizon nonlinear model predictive control,” Automatica, vol. 50, no. 9, pp. 2269–2280, 2014.
    57. F. Bayer, M. A. Müller, and F. Allgöwer, “Tube-based Robust Economic Model Predictive Control,” J.\ Proc.\ Contr., vol. 24, no. 8, pp. 1237–1246, 2014.
    58. F. D. Brunner, M. Lazar, and F. Allgöwer, “Stabilizing model predictive control: On the enlargement of the terminal set,” Int.\ J.\ Robust and Nonlinear Control, vol. 25, no. 15, pp. 2646–2670, 2014.
    59. M. Löhning, M. Reble, J. Hasenauer, S. Yu, and F. Allgöwer, “Model predictive control using reduced order models: Guaranteed stability for constrained linear systems,” J.\ Proc.\ Contr., vol. 24, no. 11, pp. 1647–1659, 2014.
    60. M. A. Müller, D. Angeli, F. Allgöwer, R. Amrit, and J. B. Rawlings, “Convergence in economic model predictive control with average constraints,” Automatica, vol. 50, no. 12, pp. 3100–3111, 2014.
    61. R. Krause et al., “Scientific workflows for bone remodelling simulations,” Proceedings in Applied Mathematics and Mechanics, 2013.
    62. M. Reble, D. E. Quevedo, and F. Allgöwer, “Control over Erasure Channels: Stochastic Stability and Performance  of Packetized Unconstrained Model Predictive Control,” Int. J. Robust and Nonlinear Control, vol. 23, no. 10, pp. 1151–1167, 2013.
    63. D. Zelazo, M. Bürger, and F. Allgöwer, “A Finite-Time Dual Method For Negotiation Between Dynamical Systems,” SIAM J. Control Optim., vol. 51, no. 1, pp. 172–194, 2013.
    64. S. Schuler, D. Schlipf, P. W. Cheng, and F. Allgöwer, “$\ell_1$-Optimal Control of Large Wind Turbines,” IEEE Trans. Cont. Sys. Tech., vol. 21, no. 4, pp. 1079–1089, 2013.
    65. R. Blind and F. Allgöwer, “On Time-Triggered and Event-Based Control of Integrator Systems over  a Shared Communication System,” Mathematics of Control, Signals, and Systems, vol. 25, no. 4, pp. 517–557, 2013.
    66. M. A. Müller, D. Angeli, and F. Allgöwer, “Economic model predictive control with self-tuning terminal cost,” European J. Control, vol. 19, no. 5, pp. 408–416, 2013.
    67. R. Blind and F. Allgöwer, “On the Optimization of the Transport Layer for Networked Control  Systems,” at-Automatisierungstechnik, vol. 61, no. 7, pp. 495–505, 2013.
    68. M. Bürger, D. Zelazo, and F. Allgöwer, “Hierarchical Clustering of Dynamical Networks Using a Saddle-Point  Analysis,” IEEE Trans. Automat. Control, vol. 58, no. 1, pp. 113–124, 2013.
    69. D. Zelazo, S. Schuler, and F. Allgöwer, “Performance and design of cycles in consensus networks,” Syst. Contr. Lett., vol. 62, no. 1, pp. 85–96, 2013.
    70. P. Wieland, J. Wu, and F. Allgöwer, “On synchronous steady states and internal models of diffusively coupled  systems,” IEEE Trans. Automat. Control, vol. 58, no. 10, pp. 2591–2602, 2013.
    71. S. Yu, C. Maier, H. Chen, and F. Allgöwer, “Tube MPC scheme based on robust control invariant set with application  to Lipschitz nonlinear systems,” Syst. Contr. Lett., vol. 62, no. 2, pp. 194–200, 2013.
    72. D. Schittler, F. Allgöwer, and R. J. De Boer, “A new model to simulate and analyze proliferating cell populations  in BrdU labeling experiments,” BMC Systems Biology (Suppl.: Selected articles from the 10th International  Workshop on Computational Systems Biology (WSCB) 2013), vol. 7(Suppl 1):S4, 2013.
    73. M. Reble, D. E. Quevedo, and F. Allgöwer, “Control over Erasure Channels: Stochastic Stability and Performance of Packetized Unconstrained Model Predictive Control,” Int.\ J.\ Robust and Nonlinear Control, vol. 23, no. 10, pp. 1151–1167, 2013.
    74. S. Schuler, D. Schlipf, P. W. Cheng, and F. Allgöwer, “$\ell_1$-Optimal Control of Large Wind Turbines,” IEEE Trans. Cont. Sys. Tech., vol. 21, no. 4, pp. 1079–1089, 2013.
    75. R. Blind and F. Allgöwer, “On Time-Triggered and Event-Based Control of Integrator Systems over a Shared Communication System,” Mathematics of Control, Signals, and Systems, vol. 25, no. 4, pp. 517–557, 2013.
    76. D. Zelazo, S. Schuler, and F. Allgöwer, “Performance and design of cycles in consensus networks,” Syst.\ Contr.\ Lett., vol. 62, no. 1, pp. 85–96, 2013.
    77. P. Wieland, J. Wu, and F. Allgöwer, “On synchronous steady states and internal models of diffusively coupled systems,” IEEE Trans.\ Automat.\ Control, vol. 58, no. 10, pp. 2591–2602, 2013.
    78. M. A. Müller, M. Reble, and F. Allgöwer, “Cooperative control of dynamically decoupled systems via distributed  model predictive control,” Int. J. Robust and Nonlinear Control, vol. 22, no. 12, pp. 1376–1397, 2012.
    79. M. Reble and F. Allgöwer, “Unconstrained Model Predictive Control and Suboptimality Estimates  for Nonlinear Continuous-Time Systems,” Automatica, vol. 48, no. 8, pp. 1812–1817, 2012.
    80. M. A. Müller and F. Allgöwer, “Improving performance in model predictive control: Switching cost  functionals under average dwell-time,” Automatica, vol. 48, no. 2, pp. 402–409, 2012.
    81. M. Daub, S. Waldherr, F. Allgöwer, P. Scheurich, and G. Schneider, “Death wins against life in a spatially extended model of the caspase-3/8  feedback loop,” Biosystems, vol. 108, pp. 45–51, 2012.
    82. S. Yu, C. Böhm, H. Chen, and F. Allgöwer, “Model predictive control of constrained LPV systems,” Int. J. Control, vol. 85, no. 6, pp. 671–683, 2012.
    83. J. Hasenauer, D. Schittler, and F. Allgöwer, “Analysis and simulation of division- and label-structured population  models,” Bulletin of Mathematical Biology, vol. 74, no. 11, pp. 2692–2732, 2012.
    84. R. Krause, D. Schittler, S. Waldherr, F. Allgöwer, B. Markert, and W. Ehlers, “Remodelling Processes in Bone: A Biphasic Porous Media Model,” Proceedings in Applied Mathematics and Mechanics, vol. 12, no. 1, pp. 131–132, 2012.
    85. J. Hasenauer, J. Heinrich, M. Doszczak, P. Scheurich, D. Weiskopf, and F. Allgöwer, “A visual analytics approach for models of heterogeneous cell populations,” EURASIP J. Bioinformatics and Systems Biology, vol. 2012, no. 2012, p. 4, 2012.
    86. C. Böhm, M. Lazar, and F. Allgöwer, “Stability of periodically time-varying systems: Periodic Lyapunov  functions,” Automatica, vol. 48, no. 10, pp. 2663–2669, 2012.
    87. J. Hasenauer, M. Löhning, M. Khammash, and F. Allgöwer, “Dynamical optimization using reduced order models: A method to  guarantee performance.,” J. Proc. Contr., vol. 22, no. 8, pp. 1490–1501, 2012.
    88. M. Bürger, G. Notarstefano, F. Bullo, and F. Allgöwer, “A distributed simplex algorithm for degenerate linear programs and  multi-agent assignments,” Automatica, vol. 48, no. 9, pp. 2298–2304, 2012.
    89. M. A. Müller, P. Martius, and F. Allgöwer, “Model predictive control of switched nonlinear systems under average  dwell-time,” J. Proc. Contr., vol. 22, no. 9, pp. 1702–1710, 2012.
    90. M. A. Müller, M. Reble, and F. Allgöwer, “Cooperative control of dynamically decoupled systems via distributed model predictive control,” Int.\ J.\ Robust and Nonlinear Control, vol. 22, no. 12, pp. 1376–1397, 2012.
    91. M. Reble and F. Allgöwer, “Unconstrained Model Predictive Control and Suboptimality Estimates for Nonlinear Continuous-Time Systems,” Automatica, vol. 48, no. 8, pp. 1812–1817, 2012.
    92. P. Wieland, R. Sepulchre, and F. Allgöwer, “An internal model principle is necessary and sufficient for linear  output synchronization,” Automatica, vol. 47, no. 5, pp. 1068–1074, 2011.
    93. R. Krause et al., “Bone remodelling: A combined biomechanical and systems-biological  challenge,” PAMM, vol. 11, no. 1, pp. 99--100, 2011.
    94. J. Hasenauer, S. Waldherr, M. Doszczak, N. Radde, P. Scheurich, and F. Allgöwer, “Analysis of heterogeneous cell populations: A density-based modeling  and identification framework,” J. Proc. Contr., vol. 21, no. 10, pp. 1417–1425, 2011.
    95. S. Waldherr, D. Dylus, and F. Allgöwer, “Bifurcation search via feedback loop breaking in biochemical signaling  pathways with time delay,” Asian J. Control, vol. 13, no. 5, pp. 691--700, 2011.
    96. S. Waldherr and F. Allgöwer, “Robust stability and instability of biochemical networks with parametric  uncertainty,” Automatica, vol. 47, pp. 1139–1146, 2011.
    97. G. Goebel, U. Münz, and F. Allgöwer, “$L_2$-Gain-based controller design for linear systems  with distributed input delay,” IMA J. of Mathematical Control and Information, vol. 28, no. 2, pp. 225–237, 2011.
    98. M. Reble, R. M. Esfanjani, S. K. Y. Nikravesh, and F. Allgöwer, “Model Predictive Control of Constrained Nonlinear Time-Delay Systems,” IMA J. of Mathematical Control and Information, vol. 28, no. 2, pp. 183–201, 2011.
    99. J. Hasenauer, S. Waldherr, M. Doszczak, N. Radde, P. Scheurich, and F. Allgöwer, “Identification of models of heterogeneous cell populations from population  snapshot data,” BMC Bioinf., vol. 12, p. 125, 2011.
    100. C. Maier, C. Böhm, F. Deroo, and F. Allgöwer, “Predictive Control for Polynomial Systems Subject to State and Input  Constraints,” at-Automatisierungstechnik, vol. 59, no. 8, pp. 479--488, 2011.
    101. M. Schliemann, E. Bullinger, E. Borchers, F. Allgöwer, R. Findeisen, and P. Scheurich, “Heterogeneity Reduces Sensitivity of Cell Death for TNF-Stimuli,” BMC Sys. Biol., vol. 5, no. 1, p. 204, 2011.
    102. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Robust Consensus Controller Design for Nonlinear Relative Degree  Two Multi-Agent Systems With Communication Constraints,” IEEE Trans. Autom. Control, vol. 56, no. 1, pp. 145–151, 2011.
    103. C. Breindl, S. Waldherr, D. M. Wittmann, F. J. Theis, and F. Allgöwer, “Steady state robustness of qualitative gene regulation networks,” Int. J. Robust and Nonlinear Control, vol. 21, no. 15, pp. 1742--1758, 2011.
    104. S. Schuler, P. Li, J. Lam, and F. Allgöwer, “Design of Structured Dynamic Output Feedback Controllers for Interconnected  Systems,” Int. J. Control, vol. 84, no. 12, pp. 2081--2091, 2011.
    105. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Consensus in Multi-Agent Systems with Coupling Delays and Switching  Topology,” IEEE Trans. Autom. Control, vol. 56, no. 12, pp. 2976–2982, 2011.
    106. P. Wieland, R. Sepulchre, and F. Allgöwer, “An internal model principle is necessary and sufficient for linear output synchronization,” Automatica, vol. 47, no. 5, pp. 1068–1074, 2011.
    107. J. Hasenauer, S. Waldherr, M. Doszczak, N. Radde, P. Scheurich, and F. Allgöwer, “Analysis of heterogeneous cell populations: A density-based modeling and identification framework,” J.\ Proc.\ Contr., vol. 21, no. 10, pp. 1417–1425, 2011.
    108. S. Waldherr and F. Allgöwer, “Robust stability and instability of biochemical networks with parametric uncertainty,” Automatica, vol. 47, pp. 1139–1146, 2011.
    109. G. Goebel, U. Münz, and F. Allgöwer, “$L_2$-Gain-based controller design for linear systems with distributed input delay,” IMA J.\ of Mathematical Control and Information, vol. 28, no. 2, pp. 225–237, 2011.
    110. M. Reble, R. M. Esfanjani, S. K. Y. Nikravesh, and F. Allgöwer, “Model Predictive Control of Constrained Nonlinear Time-Delay Systems,” IMA J.\ of Mathematical Control and Information, vol. 28, no. 2, pp. 183–201, 2011.
    111. J. Hasenauer, S. Waldherr, M. Doszczak, N. Radde, P. Scheurich, and F. Allgöwer, “Identification of models of heterogeneous cell populations from population snapshot data,” BMC Bioinf., vol. 12, p. 125, 2011.
    112. C. Maier, C. Böhm, F. Deroo, and F. Allgöwer, “Predictive Control for Polynomial Systems Subject to State and Input Constraints,” at-Automatisierungstechnik, vol. 59, no. 8, pp. 479--488, 2011.
    113. S. Schuler, P. Li, J. Lam, and F. Allgöwer, “Design of Structured Dynamic Output Feedback Controllers for Interconnected Systems,” Int.\ J.\ Control, vol. 84, no. 12, pp. 2081--2091, 2011.
    114. C. Böhm, R. Findeisen, and F. Allgöwer, “Robust control of constrained sector bounded Lur’e systems with  applications to nonlinear model predictive control,” Dynamics of Continuous, Discrete and Impulsive Systems, vol. 17, no. 6, pp. 935--958, 2010.
    115. J. Hasenauer, P. Rumschinski, S. Waldherr, S. Borchers, F. Allgöwer, and R. Findeisen, “Guaranteed steady state bounds for uncertain (bio-)chemical processes  using infeasibility certificates,” J. Proc. Contr., vol. 20, no. 9, pp. 1076–1083, 2010.
    116. J. Hasenauer, S. Waldherr, K. Wagner, and F. Allgöwer, “Parameter identification, experimental design and model falsification  for biological network models using semidefinite programming,” IET Systems Biology, vol. 4, no. 2, pp. 119–130, 2010.
    117. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Delay Robustness in Consensus Problems,” Automatica, vol. 46, no. 8, pp. 1252–1265, 2010.
    118. J. Hasenauer, S. Waldherr, N. Radde, M. Doszczak, P. Scheurich, and F. Allgöwer, “A maximum likelihood estimator for parameter distributions in heterogeneous  cell populations,” Procedia Computer Science, vol. 1, no. 1, pp. 1649–1657, 2010.
    119. D. Schittler, J. Hasenauer, F. Allgöwer, and S. Waldherr, “Cell differentiation modeled via a coupled two-switch regulatory  network,” Chaos, vol. 20, no. 4, pp. 1–9, 2010.
    120. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Robust Rendezvous of Heterogeneous Euler-Lagrange Systems on Packet-Switched  Networks,” at-Automatisierungstechnik, vol. 58, no. 4, pp. 184–191, 2010.
    121. P. Wieland, J.-S. Kim, and F. Allgöwer, “On topology and dynamics of consensus among linear high-order agents,” Int. J. Systems Science, vol. 42, no. 10, pp. 1831–1842, 2010.
    122. J.-S. Kim and F. Allgöwer, “A Nonlinear Synchronization Scheme for Hindmarsh-Rose Models,” J. Electrical Engineering and Technology, vol. 5, no. 1, pp. 163–170, 2010.
    123. S. Waldherr, J. Wu, and F. Allgöwer, “Bridging time scales in cellular decision making with a stochastic  bistable switch,” BMC Sys. Biol., vol. 4, p. 108, 2010.
    124. J. Hasenauer, S. Waldherr, K. Wagner, and F. Allgöwer, “Parameter identification, experimental design and model falsification for biological network models using semidefinite programming,” IET Systems Biology, vol. 4, no. 2, pp. 119–130, 2010.
    125. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Robust Rendezvous of Heterogeneous Euler-Lagrange Systems on Packet-Switched Networks,” at-Automatisierungstechnik, vol. 58, no. 4, pp. 184–191, 2010.
    126. P. Wieland, J.-S. Kim, and F. Allgöwer, “On topology and dynamics of consensus among linear high-order agents,” Int.\ J.\ Systems Science, vol. 42, no. 10, pp. 1831–1842, 2010.
    127. T. Schweickhardt and F. Allgöwer, “On System Gains, Nonlinearity Measures, and Linear Models for Nonlinear  Systems,” IEEE Trans. Autom. Control, vol. 54, no. 1, pp. 62–78, 2009.
    128. S. Waldherr and F. Allgöwer, “Searching bifurcations in high-dimensional parameter space via a  feedback loop breaking approach,” Int. J. Systems Science, vol. 40, no. 7, pp. 769–782, 2009.
    129. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Consensus reaching in multi-agent packet-switched networks with non-linear  coupling,” Int. J. Control, vol. 82, no. 5, pp. 953–969, 2009.
    130. M. Lang, S. Waldherr, and F. Allgöwer, “Amplitude Distribution of Stochastic Oscillations in Biochemical  Networks due to Intrinsic Noise,” PMC Biophysics, vol. 2, p. 10, 2009.
    131. U. Münz, C. Ebenbauer, T. Haag, and F. Allgöwer, “Stability Analysis of Time-Delay Systems with Incommensurate Delays  using Positive Polynomials,” IEEE Trans. Autom. Control, vol. 54, no. 5, pp. 1019–1024, 2009.
    132. J. Witt et al., “Mechanism of PP2A-mediated IKK$\beta$ dephosphorylation: a systems  biological approach,” BMC Sys. Biol., vol. 3, p. 71, 2009.
    133. T. Eißing, M. Chaves, and F. Allgöwer, “Live and let die--A systems biology view on cell death,” Comp. & Chem. Eng., vol. 33, pp. 583--589, 2009.
    134. F. Dörfler, J. K. Johnsen, and F. Allgöwer, “An introduction to interconnection and damping assignment passivity-based  control in process engineering,” J. Proc. Contr., vol. 19, no. 9, pp. 1413–1426, 2009.
    135. D. Q. Mayne, S. V. Raković, R. Findeisen, and F. Allgöwer, “Robust output feedback model predictive control of constrained linear  systems: Time varying case,” Automatica, vol. 45, no. 9, pp. 2082--2087, 2009.
    136. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Consensus reaching in multi-agent packet-switched networks with non-linear coupling,” Int.\ J.\ Control, vol. 82, no. 5, pp. 953–969, 2009.
    137. J. Witt et al., “Mechanism of PP2A-mediated IKK$\beta$ dephosphorylation: a systems biological approach,” BMC Sys. Biol., vol. 3, p. 71, 2009.
    138. S. Maldonado, R. Findeisen, and F. Allgöwer, “Describing force-induced bone groth and adaptation by a mathematical  model,” J. Musculoskel. Neuronal Interact., vol. 8, no. 1, pp. 15--17, 2008.
    139. J. Maess, A. J. Fleming, and F. Allgöwer, “Simulation of Dynamics-Coupling in Piezoelectric Tube Scanners by  Reduced Order Finite Element Analysis,” Review of Scientific Instruments, vol. 79, no. 1, pp. 1–9, 2008.
    140. S. Waldherr, T. Eißing, and F. Allgöwer, “Rückkopplungen im Leben und Sterben einer Zelle: Ansätze  zur systemtheoretischen Analyse,” at-Automatisierungstechnik, vol. 56, pp. 233--240, 2008.
    141. M. Chaves, T. Eißing, and F. Allgöwer, “Bistable Biological Systems: A Characterization Through Local Compact  Input-to-State Stability,” IEEE Trans. Autom. Control, vol. 53, no. Special Issue, pp. 87–100, 2008.
    142. C. Ebenbauer and F. Allgöwer, “A Dissipation Inequality for the Minimum Phase Property,” IEEE Trans. Autom. Control, vol. 53, no. 3, pp. 821–826, 2008.
    143. S. Maldonado, R. Findeisen, and F. Allgöwer, “Understanding the process of force-induced bone growth and adaptation  through a mathematical model,” Bone, vol. 42, Supplement 1, p. S61, 2008.
    144. R. Blind, U. Münz, and F. Allgöwer, “Modeling, Analysis, and Design of Networked Control Systems using  Jump Linear Systems,” at-Automatisierungstechnik, vol. 56, no. 1, pp. 20–28, 2008.
    145. K. Yao, F. G., and F. Allgöwer, “Barrel temperature control during operation transition in injection  molding,” Control Engineering Practice, vol. 16, pp. 1259–1264, 2008.
    146. S. Maldonado, R. Findeisen, and F. Allgöwer, “Describing force-induced bone groth and adaptation by a mathematical model,” J. Musculoskel. Neuronal Interact., vol. 8, no. 1, pp. 15--17, 2008.
    147. J. Maess, A. J. Fleming, and F. Allgöwer, “Simulation of Dynamics-Coupling in Piezoelectric Tube Scanners by Reduced Order Finite Element Analysis,” Review of Scientific Instruments, vol. 79, no. 1, pp. 1–9, 2008.
    148. S. Waldherr, T. Eißing, and F. Allgöwer, “Rückkopplungen im Leben und Sterben einer Zelle: Ansätze zur systemtheoretischen Analyse,” at-Automatisierungstechnik, vol. 56, pp. 233--240, 2008.
    149. C. Ebenbauer and F. Allgöwer, “A Dissipation Inequality for the Minimum Phase Property,” IEEE Trans.\ Autom.\ Control, vol. 53, no. 3, pp. 821–826, 2008.
    150. R. Blind, U. Münz, and F. Allgöwer, “Modeling, Analysis, and Design of Networked Control Systems using Jump Linear Systems,” at-Automatisierungstechnik, vol. 56, no. 1, pp. 20–28, 2008.
    151. C. Ebenbauer and F. Allgöwer, “Stability Analysis of Constrained Control Systems: An Alternative  Approach,” Syst. Contr. Lett., vol. 56, no. 2, pp. 93–98, 2007.
    152. T. Eißing, S. Waldherr, F. Allgöwer, P. Scheurich, and E. Bullinger, “Response to Bistability in Apoptosis: Roles of Bax, Bcl-2,  and Mitochondrial Permeability Transition Pores,” Biophysical J., vol. 92, no. 9, pp. 3332--3334, 2007.
    153. T. Eißing, S. Waldherr, F. Allgöwer, P. Scheurich, and E. Bullinger, “Steady state and (bi-) stability evaluation of simple protease  signalling networks,” BioSystems, vol. 90, no. 3, pp. 591–601, 2007.
    154. Z. Nagy and F. Allgöwer, “A nonlinear model predictive control approach for robust end-point  property control of a thin-film deposition process,” Int. J. Robust and Nonlinear Control, vol. 17, no. 17, pp. 1600–1613, 2007.
    155. M. Journée, T. Schweickhardt, and F. Allgöwer, “Comparative assessment of old and new suboptimal control schemes  on three example processes,” Int. J. of Tomography & Statistics, vol. 6, no. S07, pp. 45–50, 2007.
    156. Z. Nagy, B. Mahn, R. Franke, and F. Allgöwer, “Evaluation study of an efficient output feedback nonlinear model  predictive control for temperature tracking in an industrial batch  reactor,” Control Engineering Practice, vol. 15, no. 7, pp. 839–850, 2007.
    157. C. Ebenbauer, T. Raff, and F. Allgöwer, “Certainty-Equivalence Feedback Design with Polynomial-Type Feedbacks  Which Guarantee ISS,” IEEE Trans. Autom. Control, vol. 52, no. 4, pp. 716–720, 2007.
    158. U. Münz, P. Schumm, A. Wiesebrock, and F. Allgöwer, “Motivation and Learning Progress through Educational Games,” IEEE Trans. Industrial Electronics, vol. 54, no. 6, pp. 3141–3144, 2007.
    159. T. Schweickhardt and F. Allgöwer, “Linear control of nonlinear systems based on nonlinearity measures,” J. Proc. Contr., vol. 17, no. 3, pp. 273–284, 2007.
    160. R. Lepore, A. Vande Wouwer, M. Remy, R. Findeisen, Z. K. Nagy, and F. Allgöwer, “Optimization strategies for a MMA polymerization reactor,” Comp. & Chem. Eng., vol. 31, no. 4, pp. 281–291, 2007.
    161. C. Ebenbauer and F. Allgöwer, “Stability Analysis of Constrained Control Systems: An Alternative Approach,” Syst.\ Contr.\ Lett., vol. 56, no. 2, pp. 93–98, 2007.
    162. T. Eißing, S. Waldherr, F. Allgöwer, P. Scheurich, and E. Bullinger, “Steady state and (bi-) stability evaluation of simple protease signalling networks,” BioSystems, vol. 90, no. 3, pp. 591–601, 2007.
    163. M. Journée, T. Schweickhardt, and F. Allgöwer, “Comparative assessment of old and new suboptimal control schemes on three example processes,” Int.\ J.\ of Tomography & Statistics, vol. 6, no. S07, pp. 45–50, 2007.
    164. Z. Nagy, B. Mahn, R. Franke, and F. Allgöwer, “Evaluation study of an efficient output feedback nonlinear model predictive control for temperature tracking in an industrial batch reactor,” Control Engineering Practice, vol. 15, no. 7, pp. 839–850, 2007.
    165. U. Münz, P. Schumm, A. Wiesebrock, and F. Allgöwer, “Motivation and Learning Progress through Educational Games,” IEEE Trans.\ Industrial Electronics, vol. 54, no. 6, pp. 3141–3144, 2007.
    166. R. Lepore, A. Vande Wouwer, M. Remy, R. Findeisen, Z. K. Nagy, and F. Allgöwer, “Optimization strategies for a MMA polymerization reactor,” Comp.\ & Chem.\ Eng., vol. 31, no. 4, pp. 281–291, 2007.
    167. D. Mayne, S. V. Raković, R. Findeisen, and F. Allgöwer, “Robust output feedback model predictive control of constrained linear  systems,” Automatica, vol. 42, no. 7, pp. 1217–1222, 2006.
    168. R. Bars et al., “Theory, algorithms and technology in the design of control systems,” Annual Reviews in Control, vol. 30, pp. 19–30, 2006.
    169. C. Ebenbauer and F. Allgöwer, “Analysis and design of polynomial control systems using dissipation  inequalities and sum of squares,” Comp. & Chem. Eng., vol. 30, pp. 1601–1614, 2006.
    170. T. Schweickhardt and F. Allgöwer, “A robustness approach to linear control of mildly nonlinear processes,” Int. J. Robust and Nonlinear Control, vol. 17, no. 13, pp. 1163–1182, 2006.
    171. J. M. Rieber and F. Allgöwer, “From $H_ınfty$ control to multiobjective control:  an overview,” at-Automatisierungstechnik, vol. 54, no. 9, pp. 437--449, 2006.
    172. C. Ebenbauer and F. Allgöwer, “Analysis and design of polynomial control systems using dissipation inequalities and sum of squares,” Comp.\ & Chem.\ Eng., vol. 30, pp. 1601–1614, 2006.
    173. J. M. Rieber and F. Allgöwer, “From $H_ınfty$ control to multiobjective control: an overview,” at-Automatisierungstechnik, vol. 54, no. 9, pp. 437--449, 2006.
    174. A. Stemmer, G. Schitter, J. M. Rieber, and F. Allgöwer, “Control strategies towards faster quantitative imaging in atomic  force microscopy,” European J. Control, vol. 11, no. 4–5, pp. 384--395, 2005.
    175. E. Bullinger and F. Allgöwer, “Adaptive $łambda$-tracking for nonlinear higher relative degree  systems,” Automatica, vol. 41, no. 7, pp. 1191--2000, 2005.
    176. G. L. Wang, M. Zeitz, and F. Allgöwer, “Flatness-based optimal noncausal output transitions for constrained  nonlinear systems: Case study on an isothermal continuously stirred  tank reactor,” IEE Control Theory Appl., vol. 152, no. 1, pp. 105–112, 2005.
    177. M. Diehl, R. Findeisen, H. G. Bock, J. P. Schlöder, and F. Allgöwer, “Nominal stability of the real-time iteration scheme for nonlinear  model predictive control,” IEE Control Theory Appl., vol. 152, no. 3, pp. 296–308, 2005.
    178. T. Eißing, F. Allgöwer, and E. Bullinger, “Robustness properties of apoptosis models with respect to parameter  variations and stochastic influences,” IEE Systems Biology, vol. 152, no. 4, pp. 221–228, 2005.
    179. C. Ebenbauer, T. Raff, and F. Allgöwer, “Passivity-based Feedback Design for Polynomial Control Systems,” at-Automatisierungstechnik, vol. 8, pp. 356–366, 2005.
    180. F. Allgöwer, “Editorial: Nonlinear Model Predictive Control,” IEE Control Theory Appl., vol. 152, no. 3, pp. 257–258, 2005.
    181. E. Bullinger and F. Allgöwer, “Adaptive $łambda$-tracking for nonlinear higher relative degree systems,” Automatica, vol. 41, no. 7, pp. 1191--2000, 2005.
    182. T. Eißing, F. Allgöwer, and E. Bullinger, “Robustness properties of apoptosis models with respect to parameter variations and stochastic influences,” IEE Systems Biology, vol. 152, no. 4, pp. 221–228, 2005.
    183. T. Eißing, H. Conzelmann, E. D. Gilles, F. Allgöwer, E. Bullinger, and P. Scheurich, “Bistability analyses of a caspase activation model for receptor induced  apoptosis.,” J. Biol. Chem., vol. 279, no. 35, pp. 36892–36897, 2004.
    184. G. Schitter, A. Stemmer, and F. Allgöwer, “Robust two-degree-of-freedom control of an atomic force microscope,” Asian J. Control, vol. 6, no. 2, pp. 156–163, 2004.
    185. A. Kremling et al., “A benchmark for methods in reverse engineering and model discrimination:  problem formulation and solutions,” Genome Research, vol. 14, no. 9, pp. 1773--1785, 2004.
    186. P. Schumm, T. Schweickhardt, E. Bullinger, and F. Allgöwer, “Integration und Interaktion: Möglichkeiten des Einsatzes  von Notebook und Internet in der regelungstechnischen Ausbildung,” at-Automatisierungstechnik, vol. 2, no. 2, pp. 81–89, 2004.
    187. H. Conzelmann, J. Saez-Rodriguez, T. Sauter, E. Bullinger, F. Allgöwer, and E. D. Gilles, “Reduction of mathematical models of signal transduction networks:  Simulation-based approach applied to EGF receptor signaling,” IEE Systems Biology, vol. 1, no. 1, pp. 159--169, 2004.
    188. G. Schitter, F. Allgöwer, and A. Stemmer, “A new control strategy for high-speed atomic force microscopy,” Nanotechnology, vol. 15, pp. 108–114, 2004.
    189. J. M. Rieber, H. Wehlan, and F. Allgöwer, “The ROBORACE contest,” IEEE Control Systems Magazine, vol. 24, no. 5, pp. 57--60, 2004.
    190. F. Allgöwer, R. Findeisen, and Z. Nagy, “Nonlinear Model Predictive Control: From Theory to Application,” J. Chin. Inst. Chem. Eng., vol. 35, no. 3, pp. 299–315, 2004.
    191. A. Rehm and F. Allgöwer, “$H_ınfty$ Regelung von zeitdiskreten Deskriptorsystemen,” at-Automatisierungstechnik, vol. 52, no. 9, pp. 440–445, 2004.
    192. J. M. Rieber, H. Wehlan, and F. Allgöwer, “The ROBORACE contest,” IEEE Control Systems Magazine, vol. 24, no. 5, pp. 57--60, 2004.
    193. F. Allgöwer, R. Findeisen, and Z. Nagy, “Nonlinear Model Predictive Control: From Theory to Application,” J.\ Chin.\ Inst.\ Chem.\ Eng., vol. 35, no. 3, pp. 299–315, 2004.
    194. M. Ederer, T. Sauter, E. Bullinger, E. D. Gilles, and F. Allgöwer, “An Approach for Dividing Models of Biological Reaction Networks into  Functional Units,” Simulation: Trans. Society for Modeling and Simulation International, vol. 79, no. 12, pp. 703--716, 2003.
    195. L. Magni, G. de Nicolao, R. Scattolini, and F. Allgöwer, “Robust model predictive control for nonlinear discrete-time systems,” Int. J. Robust and Nonlinear Control, vol. 13, no. 3–4, pp. 229–246, 2003.
    196. L. Imsland, R. Findeisen, E. Bullinger, F. Allgöwer, and B. A. Foss, “A note on stability, robustness and performance of output feedback  nonlinear model predictive control.,” J. Proc. Contr., vol. 13, no. 7, pp. 633–644, 2003.
    197. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “State and Output Feedback Nonlinear Model Predictive Control: An  Overview,” European J. Control, vol. 9, no. 2–3, pp. 179–195, 2003.
    198. M. Diehl et al., “An Efficient Approach for Nonlinear Model Predictive Control of Large-Scale  Systems. Part II: Experimental Evaluation Considering the Control  of a Distillation Column,” at-Automatisierungstechnik, vol. 51, no. 1, pp. 22–29, 2003.
    199. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Output Feedback Stabilization for Constrained Systems with Nonlinear  Model Predictive Control,” Int. J. Robust and Nonlinear Control, vol. 13, no. 3–4, pp. 211–227, 2003.
    200. M. Ederer, T. Sauter, E. Bullinger, E. D. Gilles, and F. Allgöwer, “An Approach for Dividing Models of Biological Reaction Networks into Functional Units,” Simulation: Trans.\ Society for Modeling and Simulation International, vol. 79, no. 12, pp. 703--716, 2003.
    201. L. Imsland, R. Findeisen, F. Allgöwer, and B. A. Foss, “Output feedback stabilization with nonlinear predictive control: Asymptotic properties,” Int.\ J.\ Modelling, Identification and Control, vol. 24, no. 3, pp. 169–179, 2003.
    202. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “State and Output Feedback Nonlinear Model Predictive Control: An Overview,” European J.\ Control, vol. 9, no. 2–3, pp. 179–195, 2003.
    203. M. Diehl et al., “An Efficient Approach for Nonlinear Model Predictive Control of Large-Scale  Systems Part I: Description of the Methodology,” at-Automatisierungstechnik, vol. 50, no. 12, pp. 557–567, 2002.
    204. A. Rehm and F. Allgöwer, “General quadratic performance analysis and synthesis of differential  algebraic equation (DAE) systems,” J. Proc. Contr., vol. 12, no. 4, pp. 467–474, 2002.
    205. M. Diehl, R. Findeisen, Z. Nagy, H. G. Bock, J. P. Schlöder, and F. Allgöwer, “Real-time optimization and Nonlinear Model Predictive Control of  Processes governed by Differential-Algebraic Equations,” J. Proc. Contr., vol. 4, no. 12, pp. 577–585, 2002.
    206. M. Diehl et al., “An Efficient Approach for Nonlinear Model Predictive Control of Large-Scale Systems Part I: Description of the Methodology,” at-Automatisierungstechnik, vol. 50, no. 12, pp. 557–567, 2002.
    207. G. Schitter, P. H. Menold, H. F. Knapp, F. Allgöwer, and A. Stemmer, “High performance feedback for fast scanning atomic force microscopes,” Review of Scientific Instruments, vol. 72, no. 8, pp. 3320–3327, 2001.
    208. G. Schitter, P. H. Menold, H. F. Knapp, F. Allgöwer, and A. Stemmer, “High performance feedback for fast scanning atomic force microscopes,” Review of Scientific Instruments, vol. 72, no. 8, pp. 3320–3327, 2001.
    209. R. Findeisen and F. Allgöwer, “A Nonlinear Model Predictive Control Scheme for the Stabilization  of Setpoint Families,” Journal A, Benelux Quarterly Journal on Automatic Control, vol. 41, no. 1, pp. 37--45, 2000.
    210. A. Rehm and F. Allgöwer, “Self-Scheduled $H_ınfty$ Output Feedback Control of Descriptor  Systems,” Comp. & Chem. Eng., vol. 24, no. 2–7, pp. 279–284, 2000.
    211. R. Findeisen and F. Allgöwer, “A Nonlinear Model Predictive Control Scheme for the Stabilization of Setpoint Families,” Journal A, Benelux Quarterly Journal on Automatic Control, vol. 41, no. 1, pp. 37--45, 2000.
    212. H. Chen and F. Allgöwer, “A quasi-infinite horizon predictive control scheme for constrained  nonlinear systems,” IEE Control Theory Appl., vol. 16, no. 3, pp. 313–319, 1999.
    213. H. Chen and F. Allgöwer, “A computationally attractive nonlinear predictive control scheme  with guaranteed stability for stable systems,” J. Proc. Contr., vol. 8, no. 5–6, pp. 475–485, 1998.
    214. H. Chen and F. Allgöwer, “A quasi-infinite horizon nonlinear model predictive control scheme  with guaranteed stability,” Automatica, vol. 34, no. 10, pp. 1205–1217, 1998.
    215. P. H. Menold, R. K. Pearson, and F. Allgöwer, “Nonlinear structure identification of chemical processes,” Comp. & Chem. Eng., vol. 21, pp. 137–142, 1997.
  2. inbook

    1. K. Kuritz, W. Halter, and F. Allgöwer, “Passivity-Based Ensemble Control for Cell Cycle Synchronization,” in Emerging Applications of Control and Systems Theory: A Festschrift in Honor of Mathukumalli Vidyasagar, R. Tempo, S. Yurkovich, and P. Misra, Eds. Cham: Springer International Publishing, 2018, pp. 1--13.
    2. C. Maier, T. Haag, U. Münz, and F. Allgöwer, “Construction of quadratic Lyapunov-Krasovskii functionals for linear  time delay systems with multiple uncertain delays,” in Mathematical Problems in Engineering and Aerospace Sciences: ICNPAA  2008, vol. 5, S. Sivasundaram, Ed. Cambridge, UK: Cambridge Scientific Publisher Ltd, 2008.
  3. incollection

    1. A. Haupt et al., “Wireless Networking for Control,” in Control Theory of Digitally Networked Dynamic Systems, J. Lunze, Ed. Springer International Publishing, 2014, pp. 325–362.
    2. M. A. Müller and F. Allgöwer, “Distributed MPC for consensus and synchronization,” in Distributed MPC Made Easy, J. M. Maestre and R. Negenborn, Eds. Springer Verlag, 2014, pp. 89–100.
    3. M. A. Müller and F. Allgöwer, “Distributed MPC for consensus and synchronization,” in Distributed MPC Made Easy, J. M. Maestre and R. Negenborn, Eds. Springer Verlag, 2014, pp. 89–100.
    4. D. Zelazo, M. Bürger, and F. Allgöwer, “Dynamic negotiation under switching communication,” in Mathematical Systems Theory - Festschrift in Honor of Uwe Helmke  on the Occasion of his Sixtieth Birthday, K. Hüper and J. Trumpf, Eds. CreateSpace, 2013, pp. 479–500.
    5. D. Zelazo, M. Bürger, and F. Allgöwer, “Dynamic negotiation under switching communication,” in Mathematical Systems Theory - Festschrift in Honor of Uwe Helmke on the Occasion of his Sixtieth Birthday, K. Hüper and J. Trumpf, Eds. CreateSpace, 2013, pp. 479–500.
    6. M. Reble and F. Allgöwer, “Design of Terminal Cost Functionals and Terminal Regions for Model  Predictive Control of Nonlinear Time-Delay Systems,” in Time Delay Systems: Methods, Applications and New Trends, vol. 423, R. Sipahi, T. Vyhlidal, P. Pepe, and S.-I. Niculescu, Eds. Springer Berlin / Heidelberg, 2012, pp. 355–366.
    7. S. Waldherr, F. Allgöwer, E. W. Jacobsen, and S. Streif, “Robustness and adaptation of biological networks under kinetic perturbations,” in Control Theory: Mathematical Perspectives on Complex Networked Systems, no. 12/2012, F. Allgöwer, V. Blondel, and U. Helmke, Eds. Oberwolfach, Germany: Mathematisches Forschungsinstitut Oberwolfach, 2012, pp. 62–63.
    8. M. Reble and F. Allgöwer, “Design of Terminal Cost Functionals and Terminal Regions for Model Predictive Control of Nonlinear Time-Delay Systems,” in Time Delay Systems: Methods, Applications and New Trends, vol. 423, R. Sipahi, T. Vyhlidal, P. Pepe, and S.-I. Niculescu, Eds. Springer Berlin / Heidelberg, 2012, pp. 355–366.
    9. S. Waldherr, F. Allgöwer, E. W. Jacobsen, and S. Streif, “Robustness and adaptation of biological networks under kinetic perturbations,” in Control Theory: Mathematical Perspectives on Complex Networked Systems, no. 12/2012, F. Allgöwer, V. Blondel, and U. Helmke, Eds. Oberwolfach, Germany: Mathematisches Forschungsinstitut Oberwolfach, 2012, pp. 62–63.
    10. S. Waldherr, J. Hasenauer, M. Doszczak, P. Scheurich, and F. Allgöwer, “Global uncertainty analysis for a model of TNF-induced NF-$\kappa$B  signalling,” in Advances in the Theory of Control, Signals and Systems with Physical  Modeling, vol. 407, J. Levine and P. Müllhaupt, Eds. Springer Berlin / Heidelberg, 2011, pp. 365--377.
    11. L. Grüne, S. Sager, F. Allgöwer, H. G. Bock, and M. Diehl, “Predictive planning and systematic action -- on the control of technical  processes,” in Production Factor Mathematics, M. Grötschel, K. Lucas, and V. Mehrmann, Eds. Springer, 2010, pp. 9–37.
    12. L. Grüne, S. Sager, F. Allgöwer, H. G. Bock, and M. Diehl, “Predictive planning and systematic action -- on the control of technical processes,” in Production Factor Mathematics, M. Grötschel, K. Lucas, and V. Mehrmann, Eds. Springer, 2010, pp. 9–37.
    13. S. Yu, H. Chen, C. Böhm, and F. Allgöwer, “Enlarging the terminal region of NMPC with parameter-dependent  control law,” in Nonlinear Model Predictive Control - Towards New Challenging Applications, vol. 384, L. Magni, D. Raimondo, and F. Allgöwer, Eds. Springer Berlin / Heidelberg, 2009, pp. 69--78.
    14. L. Grüne, S. Sager, F. Allgöwer, H. G. Bock, and M. Diehl, “Vorausschauend planen, geziehlt handeln -- über die Regelung  und Steuerung technischer Prozesse,” in Produktionsfaktor Mathematik, M. Grötschel, K. Lucas, and V. Mehrmann, Eds. Springer Berlin / Heidelberg, 2009, pp. 27--62.
    15. C. Böhm, F. Heß, R. Findeisen, and F. Allgöwer, “An NMPC approach to avoid weakly observable trajectories,” in Nonlinear Model Predictive Control - Towards New Challenging Applications, vol. 384, L. Magni, D. Raimondo, and F. Allgöwer, Eds. Springer Berlin / Heidelberg, 2009, pp. 275--284.
    16. S. Streif, S. Waldherr, F. Allgöwer, and R. Findeisen, “Steady state sensitivity analysis of biochemical reaction networks.  A brief review and new methods,” in Systems Analysis of Biological Networks, A. Jayaraman and J. Hahn, Eds. Artech House, 2009, pp. 129--148.
    17. B. Kern, C. Böhm, R. Findeisen, and F. Allgöwer, “Receding horizon control for linear periodic time-varying systems  subject to input constraints,” in Nonlinear Model Predictive Control - Towards New Challenging Applications, vol. 384, L. Magni, D. Raimondo, and F. Allgöwer, Eds. Springer Berlin / Heidelberg, 2009, pp. 109--117.
    18. C. Ebenbauer, T. Raff, and F. Allgöwer, “Dissipation inequalities in systems theory: An introduction and recent  results,” in 6th International Congress on Industrial and Applied Mathematics,  Z�rich, Switzerland, 16-20 July 2007, R. Jeltsch and G. Wanner, Eds. Zürich, Switzerland: European Mathematical Society Publishing House, 2009, pp. 23–42.
    19. C. Böhm, M. Merk, W. Fichter, and F. Allgöwer, “Spacecraft rate damping with predictive control using magnetic actuators  only,” in Nonlinear Model Predictive Control - Towards New Challenging Applications, vol. 384, L. Magni, D. Raimondo, and F. Allgöwer, Eds. Springer Berlin / Heidelberg, 2009, pp. 511--520.
    20. U. Münz, J. M. Rieber, and F. Allgöwer, “Robust Stabilization and $H_ınfty$ Control of Uncertain Distributed  Delay Systems,” in Topics in Time Delay Systems: Analysis, Algorithms, and Control, vol. 388, J. J. Loiseau, W. Michiels, S.-I. Niculescu, and R. Sipahi, Eds. Springer Berlin / Heidelberg, 2009, pp. 221–231.
    21. M. Chaves, T. Eißing, and F. Allgöwer, “Regulation of apoptosis via the NF$\kappa$B pathway: modeling and  analysis,” in Dynamics On and Of Complex Networks, N. Ganguly, A. Deutsch, and A. Mukherjee, Eds. Birkhäuser, 2009, pp. 19--34.
    22. C. Böhm, T. Raff, M. Reble, and F. Allgöwer, “LMI-based Model Predictive Control for Linear Discrete-Time Periodic  Systems,” in Nonlinear Model Predictive Control - Towards New Challenging Applications, vol. 384, L. Magni, D. Raimondo, and F. Allgöwer, Eds. Springer Berlin / Heidelberg, 2009, pp. 99–108.
    23. U. Münz, J. M. Rieber, and F. Allgöwer, “Robust Stabilization and $H_ınfty$ Control of Uncertain Distributed Delay Systems,” in Topics in Time Delay Systems: Analysis, Algorithms, and Control, vol. 388, J. J. Loiseau, W. Michiels, S.-I. Niculescu, and R. Sipahi, Eds. Springer Berlin / Heidelberg, 2009, pp. 221–231.
    24. M. Chaves, T. Eißing, and F. Allgöwer, “Regulation of apoptosis via the NF$\kappa$B pathway: modeling and analysis,” in Dynamics On and Of Complex Networks, N. Ganguly, A. Deutsch, and A. Mukherjee, Eds. Birkhäuser, 2009, pp. 19--34.
    25. C. Böhm, T. Raff, M. Reble, and F. Allgöwer, “LMI-based Model Predictive Control for Linear Discrete-Time Periodic Systems,” in Nonlinear Model Predictive Control - Towards New Challenging Applications, vol. 384, L. Magni, D. Raimondo, and F. Allgöwer, Eds. Springer Berlin / Heidelberg, 2009, pp. 99–108.
    26. J.-S. Kim and F. Allgöwer, “Nonlinear Synchronization of Coupled Oscillators: The Polynomial  Case,” in Analysis and Design of Nonlinear Control Systems, In Honor of Alberto  Isidori, A. Astolfi and L. Marconi, Eds. Springer Berlin / Heidelberg, 2008, pp. 339–351.
    27. M. Diehl, R. Findeisen, and F. Allgöwer, “A Stabilizing Real-time Implementation of Nonlinear Model Predictive  Control,” in Real-Time PDE-Constrained Optimization, L. Biegler, O. Ghattas, M. Heinkenschloss, D. Keyes, and B. van Bloem Wanders, Eds. Philadephia, PA, USA: Society for Industrial and Applied Mathematics, 2007, pp. 23–52.
    28. T. Eißing, S. Waldherr, and F. Allgöwer, “Modelling and Analysis of Cell Death Signalling,” in Biology and Control Theory: Current Challenges, vol. 357, I. Queinnec, S. Tarbouriech, G. Garcia, and S.-I. Niculescu, Eds. Springer Berlin / Heidelberg, 2007, pp. 161--180.
    29. J. Johnsen and F. Allgöwer, “Interconnection and Damping Assignment Passivity-Based Control of  a Four-Tank System,” in Lagrangian and Hamiltonian Methods for Nonlinear Control 2006, vol. 366, F. Bullo and K. Fujimoto, Eds. Springer Berlin / Heidelberg, 2007, pp. 111–122.
    30. C. Ebenbauer and F. Allgöwer, “A Dissipation Inequality for the Minimum Phase Property of Nonlinear  Control Systems,” in Advances in Control Theory and Applications, vol. 353, C. Bonivento, L. Marconi, C. Rossi, and A. Isidori, Eds. Springer Berlin / Heidelberg, 2007, pp. 71–83.
    31. J. Johnsen and F. Allgöwer, “Interconnection and Damping Assignment Passivity-Based Control of a Four-Tank System,” in Lagrangian and Hamiltonian Methods for Nonlinear Control 2006, vol. 366, F. Bullo and K. Fujimoto, Eds. Springer Berlin / Heidelberg, 2007, pp. 111–122.
    32. T. Raff, C. Ebenbauer, R. Findeisen, and F. Allgöwer, “Remarks on Moving Horizon State Estimation with Guaranteed Convergence,” in Control and Observer Design for Nonlinear Finite and Infinite Dimensional  Systems, no. 322, T. Meurer, K. Graichen, and E. D. Gilles, Eds. Springer Berlin / Heidelberg, 2005, pp. 67–80.
    33. T. Raff, R. Findeisen, C. Ebenbauer, and F. Allgöwer, “Nonlinear Model Predictive Control and Sum of Squares Techniques,” in Fast Motions in Biomechanics and Robotics - Optimization and Feedback  Control, vol. 340, M. Diehl and K. Mombaur, Eds. Springer Berlin / Heidelberg, 2005, pp. 325–344.
    34. T. Raff, C. Ebenbauer, R. Findeisen, and F. Allgöwer, “Remarks on Moving Horizon State Estimation with Guaranteed Convergence,” in Control and Observer Design for Nonlinear Finite and Infinite Dimensional Systems, no. 322, T. Meurer, K. Graichen, and E. D. Gilles, Eds. Springer Berlin / Heidelberg, 2005, pp. 67–80.
    35. T. Schweickhardt and F. Allgöwer, “Quantitative nonlinearity assessment -- An introduction to nonlinearity  measures,” in The Integration of Design and Control, M. Georgiadis and P. Seferlis, Eds. Elsevier Science, 2004, pp. 76–95.
    36. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Towards a Sampled-Data Theory for Nonlinear Model Predictive Control,” in New Trends in Nonlinear Dynamics and Control, and their Applications, vol. 295, C. Kang, M. Xiao, and W. Borges, Eds. Springer Berlin / Heidelberg, 2003, pp. 295–311.
    37. R. Findeisen and F. Allgöwer, “The Quasi-Infinite Horizon Approach to Nonlinear Model Predictive  Control,” in Nonlinear and Adaptive Control, vol. 281, A. Zinober and D. Owens, Eds. Springer Berlin / Heidelberg, 2003, pp. 89–108.
    38. R. Findeisen and F. Allgöwer, “The Quasi-Infinite Horizon Approach to Nonlinear Model Predictive Control,” in Nonlinear and Adaptive Control, vol. 281, A. Zinober and D. Owens, Eds. Springer Berlin / Heidelberg, 2003, pp. 89–108.
    39. M. Diehl et al., “Real-Time Optimization of Large Scale Process Models: Nonlinear Model  Predictive Control of a High Purity Distillation Column,” in Online Optimization of Large Scale Systems: State of the  Art, M. Grötschel, S. O. Krumke, and J. Rambau, Eds. Springer Berlin / Heidelberg, 2001, pp. 363–384.
    40. R. Findeisen and F. Allgöwer, “Nonlinear model predictive control for index--one DAE systems,” in Nonlinear Model Predictive Control, vol. 26, F. Allgöwer and A. Zheng, Eds. Basel: Birkhäuser, 2000, pp. 145--162.
    41. R. Findeisen and F. Allgöwer, “Nonlinear model predictive control for index--one DAE systems,” in Nonlinear Model Predictive Control, vol. 26, F. Allgöwer and A. Zheng, Eds. Basel: Birkhäuser, 2000, pp. 145--162.
    42. F. Allgöwer, T. A. Badgwell, J. B. Rawlings, and S. J. Wright, “Nonlinear model predictive control,” in Perspectives in Control. Plenary Lectures and Mini-Courses at the  5th European Control Conference ECC’99, Springer-Verlag, London, 1999, pp. 391–449.
    43. E. Bullinger, A. Ilchmann, and F. Allgöwer, “A Simple Adaptive Observer for Nonlinear Systems,” in Nonlinear control systems design 1998 : a proceedings volume from  the 4th IFAC Symposium, Enschede, The Netherlands, vol. 2, H. J. C. Huijberts, H. Nijmeijer, A. J. van der Schaft, and J. M. A. Scherpen, Eds. Oxford, UK: Pergamon, 1998, pp. 781–786.
    44. H. Chen and F. Allgöwer, “Nonlinear model predictive control schemes with guaranteed stability,” in Nonlinear Model Based Process Control, R. Berber and C. Kravaris, Eds. Dordrecht, The Netherlands: Kluwer Academic Publishers, 1998, pp. 465–494.
    45. H. Chen and F. Allgöwer, “Nonlinear model predictive control schemes with guaranteed stability,” in Nonlinear Model Based Process Control, R. Berber and C. Kravaris, Eds. Dordrecht, The Netherlands: Kluwer Academic Publishers, 1998, pp. 465–494.
  4. inproceedings

    1. S. Linsenmayer, B. W. Carbelli, F. Dürr, J. Falk, F. Allgöwer, and K. Rothermel, “Integration of Communication Networks and Control Systems Using a Slotted Transmission Classification Model,” in Proc.\ 16th IEEE Annual Consumer Communications Networking Conf.\ (CCNC), Las Vegas, NV, USA, 2019, pp. 1–6.
    2. J. Köhler, M. A. Müller, and F. Allgöwer, “A simple framework for nonlinear robust output-feedback MPC,” in Proc. 18th European Control Conference (ECC), Naples, Italy, 2019, pp. 793–798.
    3. T. Martin, P. N. Köhler, and F. Allgöwer, “Dissipativity and Economic Model Predictive Control for Optimal Set Operation,” in Proc.\ American Control Conf.\ (ACC), Philadelphia, USA, 2019, pp. 1020–1026.
    4. W. Halter, S. Michalowsky, and F. Allgöwer, “Extremum seeking for optimal enzyme production under cellular fitness constraints,” in Proc.\ European Control Conf.\ (ECC), Neapel, Italien, 2019.
    5. P. N. Köhler, M. A. Müller, and F. Allgöwer, “Approximate dissipativity and performance bounds for interconnected systems,” in Proc. 18th European Control Conference (ECC), Naples, Italy, 2019, pp. 787–792.
    6. J. Köhler, M. A. Müller, and F. Allgöwer, “MPC for nonlinear periodic tracking using reference generic offine computations,” in Proc.\ IFAC Conf.\ Nonlinear Model Predictive Control (NMPC), Madison, Wisconsin, 2018, pp. 656–661.
    7. J. Köhler, M. A. Müller, and F. Allgöwer, “A novel constraint tightening approach for nonlinear robust model  predictive control,” in Proc. American Control Conf. (ACC), 2018.
    8. J. Köhler, C. Enyioha, and F. Allgöwer, “Dynamic Resource Allocation to Control Epidemic Outbreaks -A Model Predictive Control Approach,” in Proc.\ American Control Conf.\ (ACC), Milwaukee, Wisconsin, 2018, pp. 1546–1551.
    9. J. Köhler, M. A. Müller, and F. Allgöwer, “Nonlinear Reference Tracking with Model Predictive Control: An Intuitive  Approach,” in Proc. European Control Conf. (ECC), 2018.
    10. P. N. Köhler, M. A. Müller, and F. Allgöwer, “Interconnections of dissipative systems and distributed economic MPC,” in Proc. 6th IFAC Conference on Nonlinear Model Predictive Control, Madison, Wisconsin, 2018, pp. 88–93.
    11. W. Halter, F. Allgöwer, R. M. Murray, and A. Gyorgy, “Optimal Experiment Design and Leveraging Competition for Shared Resources in Cell-Free Extracts,” in Proc.\ 57th IEEE Conf.\ Decision and Control (CDC), Miami Beach, USA, 2018.
    12. S. Linsenmayer and F. Allgöwer, “Performance oriented triggering mechanisms with guaranteed traffic characterization for linear discrete-time systems,” in Proc.\ European Control Conf.\ (ECC), Limassol, Cyprus, 2018, pp. 1474–1479.
    13. P. N. Köhler, M. A. Müller, and F. Allgöwer, “Transient performance of economic model predictive control with average  constraints,” in Proc. 56th IEEE Conf. Decision and Control (CDC), Melbourne, Victoria, Australia, 2017, pp. 5557–5562.
    14. W. Halter, Z. A. Tuza, and F. Allgöwer, “Signal differentiation with genetic networks,” in Proc. 20th IFAC World Congress, Toulouse, France, 2017.
    15. J. M. Montenbruck, S. Zeng, and F. Allgöwer, “Linear Systems with Quadratic Outputs,” in Proc. American Control Conf. (ACC), Seattle, WA, USA, 2017, pp. 1030–1034.
    16. S. Linsenmayer, R. Blind, and F. Allgöwer, “Delay-dependent data rate bounds for containability of scalar systems,” in Proc. of the 20th IFAC World Congress, Toulouse, France, 2017, pp. 7875–7880.
    17. J. Köhler, M. A. Müller, N. Li, and F. Allgöwer, “Real Time Economic Dispatch for power networks: A Distributed Economic  Model Predictive Control Approach,” in Proc. 56th IEEE Conf. Decision and Control (CDC), Melbourne, Victoria, Australia, 2017, pp. 6340–6345.
    18. W. Halter, J. M. Montenbruck, and F. Allgöwer, “Systems with integral resource consumption,” in Proc. 56th IEEE Conf. Decision and Control (CDC), Melbourne, Australia, 2017.
    19. S. Linsenmayer and F. Allgöwer, “Stabilization of Networked Control Systems with weakly hard real-time  dropout description,” in Proc. 56th IEEE Conf. Decision and Control (CDC), Melbourne, Australia, 2017, pp. 4765–4770.
    20. P. N. Köhler, M. A. Müller, J. Pannek, and F. Allgöwer, “On Exploitation of Supply Chain Properties by Sequential Distributed  MPC.,” in Proc. of the 20th IFAC World Congress, Toulouse, France, 2017, pp. 8219–8224.
    21. W. Halter, J. M. Montenbruck, and F. Allgöwer, “Geometric stability considerations of the ribosome flow model with  pool,” in Proc. 22nd Int. Symp. Mathematical Theory of Networks and Systems  (MTNS), Minneapolis, MN, USA, 2016, pp. 424–429.
    22. F. D. Brunner and F. Allgöwer, “A Lyapunov Function Approach to the Event-triggered Stabilization  of the Minimal Robust Positively Invariant Set,” in Proc. 6th IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), Tokyo, Japan, 2016, vol. 49, no. 22, pp. 25--30.
    23. E. Aydiner, M. A. Müller, and F. Allgöwer, “Periodic Reference Tracking for Nonlinear Systems via Model Predictive  Control,” in Proc. European Control Conf. (ECC), Aalborg, Denmark, 2016, pp. 2602--2607.
    24. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Dynamic Thresholds in Robust Event-Triggered Control for Discrete-Time  Linear Systems,” in Proc. European Control Conf. (ECC), Aalborg, Denmark, 2016, pp. 983--988.
    25. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “$\gamma$-Invasive Event-triggered and Self-triggered Control for  Perturbed Linear Systems,” in Proc. 55th IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2016, pp. 1346–1351.
    26. F. D. Brunner, W. P. . M. H. Heemels, and F. Allgöwer, “Numerical Evaluation of a Robust Self-Triggered MPC Algorithm,” in Proc. 6th IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), Tokyo, Japan, 2016, vol. 49, no. 22, pp. 151--156.
    27. S. Zeng and F. Allgöwer, “A General Sampled Observability Result and Its Applications,” in Proc. 55th IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2016, pp. 3997--4002.
    28. P. N. Köhler, M. A. Müller, and F. Allgöwer, “A distributed economic MPC scheme for coordination of self-interested  systems,” in Proc. American Control Conf. (ACC), Boston, MA, USA, 2016, pp. 889--894.
    29. S. Linsenmayer, D. V. Dimarogonas, and F. Allgöwer, “A non-monotonic approach to periodic event-triggered control with  packet loss,” in Proc. 55th IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2016, pp. 507–512.
    30. J. M. Montenbruck and F. Allgöwer, “Input-Output Control of Composite Systems,” in Proc. 55th IEEE Conf. Decision and Control (CDC), 2016.
    31. F. A. Bayer, F. D. Brunner, M. Lazar, M. G. A. Wijnand, and F. Allgöwer, “A Tube-Based Approach to Nonlinear Explicit MPC,” in Proc. 55th IEEE Conf. Decision and Control (CDC), 2016, pp. 4059--4064.
    32. J. M. Montenbruck and F. Allgöwer, “Some Problems Arising in Controller Design from Big Data via Input-Output  Methods,” in Proc. 55th IEEE Conf. Decision and Control (CDC), 2016.
    33. F. D. Brunner, F. A. Bayer, and F. Allgöwer, “Robust Steady State Optimization for Polytopic Systems,” in Proc. 55th IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2016, pp. 4084–4089.
    34. S. Zeng and F. Allgöwer, “On the Moment Dynamics of Discrete Measures,” in Proc. 55th IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2016, pp. 4901--4906.
    35. S. Knüfer, M. A. Müller, and F. Allgöwer, “Stabilizing Model Predictive Control without Terminal Constraints  for Switched Nonlinear Systems,” in Proc. 10th IFAC Symp. Nonlinear Control Systems (NOLCOS), Monterey, CA, USA, 2016, pp. 65–70.
    36. S. Zeng, H. Ishii, and F. Allgöwer, “State estimation of interconnected ensembles with anonymized outputs,” in Proc. 6th IFAC Workshop on Distributed Estimation and Control in  Networked Systems, Tokyo, Japan, 2016.
    37. F. D. Brunner, M. A. Müller, and F. Allgöwer, “Enhancing Output Feedback MPC for Linear Discrete-time Systems  with Set-valued Moving Horizon Estimation,” in Proc. 55th IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2016, pp. 2733–2738.
    38. J. M. Montenbruck, S. Zeng, and F. Allgöwer, “On the Observability Properties of Systems with Rolling Shutter,” in Proc. 54th Annual Allerton Conf. on Communication, Control, and Computing, 2016.
    39. S. K. Niederländer, A. F., and C. J., “Exponentially Fast Distributed Coordination for Nonsmooth Convex  Optimization,” in Proc. 55th IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2016, pp. 1036–1041.
    40. J. M. Montenbruck and F. Allgöwer, “Persistence of Excitation and the Feedback Theorem for Passive Systems,” in Proc. 10th IFAC Symp. Nonlinear Control Systems (NOLCOS), 2016.
    41. F. A. Bayer, M. A. Müller, and F. Allgöwer, “Min-max Economic Model Predictive Control Approaches with Guaranteed  Performance,” in Proc. 55th IEEE Conf. Decision and Control (CDC), 2016, pp. 3210--3215.
    42. G. Goebel and F. Allgöwer, “A Simple Semi-Explicit MPC Algorithm,” in Proc. IFAC Conf. Nonlinear Model Predictive Control (NMPC), Seville, Spain, 2015, vol. 48, no. 23, pp. 489–494.
    43. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Robust Event-Triggered MPC for Constrained Linear Discrete-Time  Systems with Guaranteed Average Sampling Rate,” in Proc. IFAC Conf. Nonlinear Model Predictive Control (NMPC), Seville, Spain, 2015, vol. 48, no. 23, pp. 117–122.
    44. M. A. Müller, L. Grüne, and F. Allgöwer, “On the role of dissipativity in economic model predictive control,” in Proc. 5th IFAC Conf. Nonlinear Model Predictive Control (NMPC), 2015, vol. 48, no. 23, pp. 110–116.
    45. S. Zeng, H. Ishii, and F. Allgöwer, “Sampled Observability of Discrete Heterogeneous Ensembles from Anonymized  Output Measurements,” in Proc. 54th IEEE Conf. Decision and Control (CDC), 2015, pp. 5683–5688.
    46. F. D. Brunner, T. M. P. Gommans, W. P. M. H. Heemels, and F. Allgöwer, “Resource-aware set-valued estimation for discrete-time linear systems,” in Proc. 54th IEEE Conf. Decision and Control (CDC), Osaka, Japan, 2015, pp. 5480–5486.
    47. J. M. Montenbruck, H.-B. Dürr, C. Ebenbauer, and F. Allgöwer, “Extremum Seeking with Drift,” in Proc. 1st MICNON, St. Petersburg, Russia, 2015, vol. 48, no. 11, pp. 126–130.
    48. J. M. Montenbruck, M. Bürger, and F. Allgöwer, “Navigation and Obstacle Avoidance via Backstepping for Mechanical  Systems with Drift in the Closed Loop,” in Proc. 2015 American Control Conference, Chicago, IL, USA, 2015, pp. 625–630.
    49. G. Seyboth and F. Allgöwer, “Output Synchronization of Linear Multi-Agent Systems under Constant  Disturbances via Distributed Integral Action,” in Proc. American Control Conf. (ACC), Chicago, IL, USA, 2015, pp. 62–67.
    50. S. Zeng, H. Ishii, and F. Allgöwer, “On the state estimation problem for discrete ensembles from discrete-time  output snapshots,” in Proc. American Control Conf. (ACC), Chicago, IL, USA, 2015, pp. 4844–4849.
    51. J. M. Montenbruck, D. Zelazo, and F. Allgöwer, “Retraction Balancing and Formation Control,” in Proc. 54th IEEE Conf. Decision and Control (CDC), Osaka, Japan, 2015, pp. 3645–3650.
    52. J. M. Montenbruck, A. Birk, and F. Allgöwer, “A Convex Conic Underestimate of Laplacian Spectra and its Application  to Network Synthesis,” in Proc. European Control Conf. (ECC), Linz, Austria, 2015, pp. 563–568.
    53. J. M. Montenbruck, M. Arcak, and F. Allgöwer, “Stabilizing Submanifolds with Passive Input-Output Relations,” in Proc. 54th IEEE Conf. Decision and Control (CDC), Osaka, Japan, 2015, pp. 4381–4387.
    54. R. Blind and F. Allgöwer, “Towards Networked Control Systems with Guaranteed Stability: Using  Weakly Hard Real-Time Constraints to Model the Loss Process,” in Proc. 54th IEEE Conf. Decision and Control (CDC), Osaka, Japan, 2015, pp. 7510–7515.
    55. F. A. Bayer, M. A. Müller, and F. Allgöwer, “Average Constraints in Robust Economic Model Predictive Control,” in Proc. IFAC Int. Symp. Advanced Control of Chemical Processes (ADCHEM), Whistler, Britisch Columbia, Canada, 2015, pp. 44–49.
    56. M. Lorenzen, F. Allgöwer, F. Dabbene, and R. Tempo, “An Improved Constraint-Tightening Approach for Stochastic MPC,” in Proc. American Control Conf. (ACC), Chicago, IL, USA, 2015, pp. 944–949.
    57. F. D. Brunner, T. M. P. Gommans, W. P. M. H. Heemels, and F. Allgöwer, “Communication Scheduling in Robust Self-Triggered MPC for Linear  Discrete-Time Systems,” in Proc. 5th IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), Philadelphia, PA, USA, 2015, vol. 48, no. 22, pp. 132–137.
    58. J. M. Montenbruck, G. S. Schmidt, A. Kecskeméthy, and F. Allgöwer, “Two Gradient-Based Control Laws on SE(3) Derived from Distance  Functions,” in Interdisciplinary Applications of Kinematic, 2015, vol. 2, pp. 31–41.
    59. S. Linsenmayer, D. V. Dimarogonas, and F. Allgöwer, “Nonlinear Event-Triggered Platooning Control with Exponential Convergence,” in Proc. 5th IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), Philadelphia, PA, USA, 2015, vol. 48, no. 22, pp. 138–143.
    60. J. Wu, L. Li, V. Ugrinovskii, and F. Allgöwer, “Distributed filter design for cooperative $H_ınfty$-type estimation,” in Proc. IEEE Multiconf. Systems and Control (MSC), Sydney, Australia, 2015, pp. 1373–1378.
    61. F. A. Bayer, M. Lorenzen, M. A. Müller, and F. Allgöwer, “Improving Performance in Robust Economic MPC Using Stochastic Information,” in Proc. IFAC Conf. Nonlinear Model Predictive Control (NMPC), Seville, Spain, 2015, vol. 48, no. 23, pp. 410–415.
    62. S. Zeng and F. Allgöwer, “On the ensemble observability problem for nonlinear systems,” in Proc. 54th IEEE Conf. Decision and Control (CDC), 2015, pp. 6318–6323.
    63. W. Halter, N. Kress, K. Otte, S. Reich, B. Hauer, and F. Allgöwer, “Yield-Analysis of Different Coupling Schemes for Interconnected Bio-Reactors,” in Proc. SIAM Conf. Control and its Applications, Paris, France, 2015, pp. 384–391.
    64. J. Wu, V. Ugrinovskii, and F. Allgöwer, “Cooperative $H_ınfty$ estimation for large-scale interconnected  linear systems,” in Proc. American Control Conf. (ACC), Chicago, IL, USA, 2015, pp. 2119–2124.
    65. M. Lorenzen, F. Allgöwer, F. Dabbene, and R. Tempo, “Scenario-Based Stochastic MPC with Guaranteed Recursive Feasibility,” in Proc. 54th IEEE Conf. Decision and Control (CDC), Osaka, Japan, 2015, pp. 4958–4963.
    66. E. Aydiner, F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Robust Self-Triggered Model Predictive Control for Constrained Discrete-Time  LTI Systems based on Homothetic Tubes,” in Proc. European Control Conf. (ECC), Linz, Austria, 2015, pp. 1587–1593.
    67. M. A. Müller, L. Grüne, and F. Allgöwer, “On the role of dissipativity in economic model predictive control,” in Proc.\ 5th IFAC Conf.\ Nonlinear Model Predictive Control (NMPC), 2015, pp. 110–116.
    68. J. M. Montenbruck, M. Bürger, and F. Allgöwer, “Navigation and Obstacle Avoidance via Backstepping for Mechanical Systems with Drift in the Closed Loop,” in Proc.\ 2015 American Control Conference, Chicago, IL, USA, 2015, pp. 625–630.
    69. G. Seyboth and F. Allgöwer, “Output Synchronization of Linear Multi-Agent Systems under Constant Disturbances via Distributed Integral Action,” in Proc.\ American Control Conf.\ (ACC), Chicago, IL, USA, 2015, pp. 62–67.
    70. J. M. Montenbruck, A. Birk, and F. Allgöwer, “A Convex Conic Underestimate of Laplacian Spectra and its Application to Network Synthesis,” in Proc.\ European Control Conf.\ (ECC), Linz, Austria, 2015.
    71. F. D. Brunner, T. M. P. Gommans, W. P. M. H. Heemels, and F. Allgöwer, “Communication Scheduling in Robust Self-Triggered MPC for Linear Discrete-Time Systems,” in Proc.\ 5th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), Philadelphia, PA, USA, 2015.
    72. F. A. Bayer, M. Lorenzen, M. A. Müller, and F. Allgöwer, “Improving Performance in Robust Economic MPC Using Stochastic Information,” in Proc.\ IFAC Conf.\ Nonlinear Model Predictive Control (NMPC ’15), Seville, Spain, 2015, pp. 411–416.
    73. W. Halter, N. Kress, K. Otte, S. Reich, B. Hauer, and F. Allgöwer, “Yield-Analysis of Different Coupling Schemes for Interconnected Bio-Reactors,” in Proc.\ SIAM Conf.\ Control and its Applications, Paris, France, 2015.
    74. J. Wu, V. Ugrinovskii, and F. Allgöwer, “Cooperative $H_ınfty$ estimation for large-scale interconnected linear systems,” in Proc.\ American Control Conf.\ (ACC), Chicago, IL, USA, 2015, pp. 2119--2124.
    75. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Robust Self-Triggered MPC for Constrained Linear Systems,” in Proc. European Control Conf. (ECC), Strasbourg, France, 2014, pp. 472–477.
    76. F. Bayer, M. A. Müller, and F. Allgöwer, “Set-based Disturbance Attenuation in Economic Model Predictive Control,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 1898–1903.
    77. M. A. Müller and F. Allgöwer, “Distributed economic MPC: a framework for cooperative control problems,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 1029–1034.
    78. R. M. Schaich, M. A. Müller, and F. Allgöwer, “A distributed model predictive control scheme for networks with communication  failure,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 12004–12009.
    79. R. Blind and F. Allgöwer, “On the stabilizability of continuous-time systems over a packet based  communication system with loss and delay,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 6466–6471.
    80. S. Waldherr, S. Zeng, and F. Allgöwer, “Identifiability of population models via a measure theoretical approach,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 1717–1722.
    81. J. Wu, V. Ugrinovskii, and F. Allgöwer, “Cooperative estimation for synchronization of heterogeneous multi-agent  systems using relative information,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 4662–4667.
    82. G. Seyboth and F. Allgöwer, “Synchronized model matching: a novel approach to cooperative control  of nonlinear multi-agent systems,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 1985–1990.
    83. G. Goebel and F. Allgöwer, “Improved state dependent parametrizations including a piecewise linear  feedback for constrained linear MPC,” in Proc. American Control Conf. (ACC), Portland, OR, USA, 2014, pp. 4192–4197.
    84. M. A. Müller, D. Angeli, and F. Allgöwer, “Performance analysis of economic MPC with self-tuning terminal  cost,” in Proc. American Control Conf. (ACC), Portland, OR, USA, 2014, pp. 2845–2850.
    85. G. Goebel and F. Allgöwer, “State Dependent Parametrizations for Nonlinear MPC,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 1005–1010.
    86. S. Zeng, S. Waldherr, and F. Allgöwer, “An inverse problem of tomographic type in population dynamics,” in Proc. 53rd IEEE Conf. Decision and Control (CDC), Los Angeles, CA, USA, 2014, pp. 1643–1648.
    87. M. Bürger, C. De Persis, and F. Allgöwer, “Optimal Pricing Control in Distribution Networks With Time-varying  Supply and Demand,” in Proc. 21st Int. Symp. Mathematical Theory of Networks and Systems  (MTNS), Groningen, The Netherlands, 2014, pp. 584–591.
    88. J. M. Montenbruck and F. Allgöwer, “Pinning Capital Stock and Gross Investment Rate in Competing Rationally  Managed Firms,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 10719–10724.
    89. G. Goebel and F. Allgöwer, “Increasing performance of parametrizations for linear MPC via application  of a data mining algorithm,” in Proc. 53rd IEEE Conf. Decision and Control (CDC), Los Angeles, CA, USA, 2014, pp. 4932–4937.
    90. J. M. Montenbruck, H.-B. Dürr, C. Ebenbauer, and F. Allgöwer, “Extremum Seeking and Obstacle Avoidance on the Special Orthogonal  Group,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 8229–8234.
    91. F. D. Brunner and F. Allgöwer, “Approximate Predictive Control of Polytopic Systems,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 11060--11066.
    92. F. Bayer and F. Allgöwer, “Robust Economic Model Predictive Control with Linear Average Constraints,” in Proc. 53rd IEEE Conf. Decision and Control (CDC), Los Angeles, CA, USA, 2014, pp. 6707–6712.
    93. F. D. Brunner, M. Lazar, and F. Allgöwer, “Computation of piecewise affine terminal cost functions for model  predictive control,” in Proc. 17th Int. Conf. Hybrid Systems: Computation and Control (HSCC), Berlin, Germany, 2014, pp. 1–10.
    94. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Robust Self-Triggered MPC for Constrained Linear Systems,” in Proc.\ European Control Conf.\ (ECC), Strasbourg, France, 2014, pp. 472–477.
    95. R. M. Schaich, M. A. Müller, and F. Allgöwer, “A distributed model predictive control scheme for networks with communication failure,” in Proc.\ 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 12004–12009.
    96. R. Blind and F. Allgöwer, “On the stabilizability of continuous-time systems over a packet based communication system with loss and delay,” in Proc.\ 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 6466–6471.
    97. S. Waldherr, S. Zeng, and F. Allgöwer, “Identifiability of population models via a measure theoretical approach,” in Proc.\ 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 1717–1722.
    98. S. Zeng, S. Waldherr, and F. Allgöwer, “An inverse problem of tomographic type in population dynamics,” in Proc.\ 53rd IEEE Conf.\ Decision and Control (CDC), Los Angeles, CA, USA, 2014, pp. 1643–1648.
    99. M. Bürger, C. De Persis, and F. Allgöwer, “Optimal Pricing Control in Distribution Networks With Time-varying Supply and Demand,” in Proc.\ 21st Int.\ Symp.\ Mathematical Theory of Networks and Systems (MTNS), Groningen, The Netherlands, 2014.
    100. M. Lorenzen, M. Bürger, G. Notarstefano, and F. Allgöwer, “A Distributed Solution to the Adjustable Robust Economic Dispatch  Problem,” in Proc. 4th IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), 2013, pp. 75–80.
    101. F. Bayer, M. Bürger, and F. Allgöwer, “Discrete-time Incremental ISS: A Framework for Robust NMPC,” in Proc. European Control Conf. (ECC), Zurich, Switzerland, 2013, pp. 2068–2073.
    102. F. Bayer, G. Notarstefano, and F. Allgöwer, “A Projected SQP Method for Nonlinear Optimal Control with Quadratic  Convergence,” in Proc. 52nd IEEE Conf. Decision and Control (CDC), Florence, Italy, 2013, pp. 6463–6468.
    103. J. Wu, J. Qin, B. Yu, and F. Allgöwer, “Leaderless synchronization of linear multi-agent systems under directed  switching topologies: an invariance approach,” in Proc. 52nd IEEE Conf. Decision and Control (CDC), Florence, Italy, 2013, pp. 6043–6048.
    104. F. D. Brunner, M. Lazar, and F. Allgöwer, “An Explicit Solution to Constrained Stabilization via Polytopic Tubes,” in Proc. 52nd IEEE Conf. Decision and Control (CDC), Florence, Italy, 2013, pp. 7721–7727.
    105. G. S. Schmidt, C. Ebenbauer, and F. Allgöwer, “Output regulation for attitude control: a global approach,” in Proc. American Control Conf. (ACC), Washington, D.C., USA, 2013, pp. 5251–5256.
    106. M. A. Müller, D. Liberzon, and F. Allgöwer, “Norm-controllability, or how a nonlinear system responds to large  inputs,” in Proc. 9th IFAC Symp. Nonlinear Control Systems (NOLCOS), 2013, pp. 104–109.
    107. C. Breindl, M. Chaves, and F. Allgöwer, “A linear reformulation of Boolean optimization problems and structure  identification of gene regulation networks,” in Proc. 52nd IEEE Conf. Decision and Control (CDC), 2013, pp. 733--738.
    108. R. Blind and F. Allgöwer, “Retransmitting Lost Measurements to Improve Remote Estimation,” in Proc. American Control Conf. (ACC), Washington, D.C., USA, 2013, pp. 4154–4158.
    109. M. Bürger, Z. D., and F. Allgöwer, “On the Steady-State Inverse-Optimality of Passivity-based Cooperative  Control.,” in Proc. 4th IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), Koblenz, 2013, pp. 138–143.
    110. G. Goebel and F. Allgöwer, “Obtaining and employing state dependent parametrizations of prespecified  complexity in constrained MPC,” in Proc. 52nd IEEE Conf. Decision and Control (CDC), Florence, Italy, 2013, pp. 7077–7082.
    111. J. M. Montenbruck, M. Bürger, and F. Allgöwer, “Practical Cluster Synchronization of Heterogeneous Systems on Graphs  with Acyclic Topology,” in Proc. 52nd IEEE Conf. on Decision and Control (CDC), Florence, Italy, 2013, pp. 692–697.
    112. J. M. Montenbruck, G. S. Seyboth, and F. Allgöwer, “Practical and Robust Synchronization of Systems with Additive Linear  Uncertainties,” in Proc. 9th IFAC Symp. Nonlinear Control Systems (NOLCOS), Toulouse, France, 2013, pp. 743–748.
    113. M. A. Müller, D. Angeli, and F. Allgöwer, “On convergence of averagely constrained economic MPC and necessity  of dissipativity for optimal steady-state operation,” in Proc. American Control Conf. (ACC), 2013, pp. 3147–3152.
    114. G. Seyboth and F. Allgöwer, “Clock Synchronization over Directed Graphs,” in Proc. 52nd IEEE Conf. Decision and Control (CDC), Florence, Italy, 2013, pp. 6105–6111.
    115. R. Blind and F. Allgöwer, “On the Joint Design of Controller and Routing for Networked Control  Systems,” in Proc. 4th IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), Koblenz, Germany, 2013, pp. 240–246.
    116. F. D. Brunner, M. Lazar, and F. Allgöwer, “Stabilizing Linear Model Predictive Control: On the Enlargement of  the Terminal Set,” in Proc. European Control Conf. (ECC), Zurich, Switzerland, 2013, pp. 511–517.
    117. M. Bürger, G. Notarstefano, and F. Allgöwer, “From Non-cooperative to Cooperative Distributed MPC: A Simplicial  Approximation Perspective,” in Proc. European Control Conf. (ECC), Zurich, Switzerland, 2013, pp. 2795–2800.
    118. D. Schittler, F. Allgöwer, and S. Waldherr, “Multistability equivalence between gene regulatory networks of different  dimensionality,” in Proc. European Control Conf. (ECC), Zurich, Switzerland, 2013, pp. 3640–3645.
    119. M. A. Müller, D. Angeli, and F. Allgöwer, “Economic model predictive control with transient average constraints,” in Proc. 52nd IEEE Conf. Decision and Control (CDC), Florence, Italy, 2013, pp. 5119–5124.
    120. M. A. Müller, D. Angeli, and F. Allgöwer, “Economic model predictive control with self-tuning terminal weight,” in Proc. European Control Conf. (ECC), Zurich, Switzerland, 2013, pp. 2044–2049.
    121. S. Schuler, D. Zelazo, and F. Allgöwer, “Robust Design of Sparse Relative Sensing Networks,” in Proc. European Control Conference (ECC), Zurich, Switzerland, 2013, pp. 1860–1865.
    122. C. Breindl, M. Chaves, and F. Allgöwer, “A linear reformulation of Boolean optimization problems and structure identification of gene regulation networks,” in Proc.\ 52nd IEEE Conf.\ Decision and Control (CDC), 2013, pp. 733--738.
    123. R. Blind and F. Allgöwer, “On the Joint Design of Controller and Routing for Networked Control Systems,” in Proc.\ 4th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), Koblenz, Germany, 2013, pp. 240–246.
    124. M. Bürger, G. Notarstefano, and F. Allgöwer, “From Non-cooperative to Cooperative Distributed MPC: A Simplicial Approximation Perspective,” in Proc.\ European Control Conf.\ (ECC), Zurich, Switzerland, 2013, pp. 2795–2800.
    125. G. Seyboth, G. S. Schmidt, and F. Allgöwer, “Cooperative Control of Linear Parameter-Varying Systems,” in Proc. American Control Conf. (ACC), Montreal, Canada, 2012, pp. 2407–2412.
    126. D. Zelazo, A. Franchi, F. Allgöwer, H. H. Bülthoff, and P. Robuffo Giordano, “Rigidity Maintenance Control for Multi-robot Systems,” in Proc. Robotics: Science and Systems, Sydney, Australia, 2012.
    127. G. S. Schmidt, C. Ebenbauer, and F. Allgöwer, “A solution for a class of output regulation problems on SO(n),” in Proc. American Control Conf. (ACC), Montreal, Canada, 2012, pp. 1773–1779.
    128. R. Blind and F. Allgöwer, “Is it Worth to Retransmit Lost Packets in Networked Control Systems?,” in Proc. 51th IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 1368–1373.
    129. S. Waldherr, J. Hasenauer, and F. Allgöwer, “Set based uncertainty analysis and parameter estimation of biological  networks with the BioSDP toolbox,” in Proc. 9th Int. Workshop on Computational Systems Biology (WCSB), Ulm, Germany, 2012.
    130. D. Zelazo, S. Schuler, and F. Allgöwer, “Cycles and Sparse Design of Consensus Networks,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 3808–3813.
    131. J. Wu and F. Allgöwer, “A Constructive Approach to Synchronization Using Relative Information,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 5960–5965.
    132. S. Schuler, D. Zelazo, and F. Allgöwer, “Design of Sparse Relative Sensing Networks,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 2749–2754.
    133. G. Seyboth, G. S. Schmidt, and F. Allgöwer, “Output Synchronization of Linear Parameter-varying Systems via Dynamic  Couplings,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 5128–5133.
    134. D. Zelazo and F. Allgöwer, “Growing Optimally Rigid Formations,” in Proc. American Control Conf. (ACC), Montreal, Canada, 2012, pp. 3901–3906.
    135. M. Bürger, D. Zelazo, and F. Allgöwer, “Combinatorial Insights and Robustness Analysis for Clustering in  Dynamical Networks,” in Proc. American Control Conf. (ACC), Montreal, Canada, 2012, pp. 454–459.
    136. D. Zelazo and F. Allgöwer, “Eulerian Consensus Networks,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 4715–4720.
    137. R. Blind and F. Allgöwer, “The Performance of Event-Based Control for Scalar Systems with Packet  Losses,” in Proc. 51th IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 6572–6576.
    138. M. A. Müller, B. Schürmann, and F. Allgöwer, “Robust cooperative control of dynamically decoupled systems via distributed  MPC,” in Proc. IFAC Conf. Nonlinear Model Predictive Control (NMPC), Noordwijkerhout, The Netherlands, 2012, pp. 412–417.
    139. M. Bürger, G. Notarstefano, and F. Allgöwer, “Distributed Robust Optimization via Cutting-Plane Consensus,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 7457–7463.
    140. M. Reble, D. E. Quevedo, and F. Allgöwer, “A Unifying Framework for Stability in MPC using a Generalized Integral  Terminal Cost,” in Proc. American Control Conf. (ACC), Montreal, Canada, 2012, pp. 1211–1216.
    141. D. Schittler, J. Hasenauer, and F. Allgöwer, “A model for proliferating cell populations that accounts for cell  types,” in Proc. 9th Int. Workshop on Computational Systems Biology (WCSB), Ulm, Germany, 2012, pp. 84–87.
    142. M. A. Müller and F. Allgöwer, “Robustness of steady-state optimality in economic model predictive  control,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 1011–1016.
    143. B. W. Carabelli et al., “Exact Convex Formulations of Network-Oriented Optimal Operator Placement,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 3777–3782.
    144. M. A. Müller, D. Liberzon, and F. Allgöwer, “Relaxed conditions for norm-controllability of nonlinear systems,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 314–319.
    145. S. Schuler, U. Münz, and F. Allgöwer, “Decentralized State Feedback Control for Interconnected Process Systems,” in Proc. 8th IFAC Symposium on Advanced Control of Chemical Processes  (AdChem), Singapore, 2012, pp. 1–10.
    146. C. Breindl, M. Chaves, J. L. Gouzé, and F. Allgöwer, “Structure estimation for unate Boolean models of gene regulation  networks,” in Proc. 16th IFAC Symp. System Identification (SYSID), Brussels, Belgium, 2012, pp. 1725--1730.
    147. M. Reble, D. E. Quevedo, and F. Allgöwer, “Improved Stability Conditions for Unconstrained Nonlinear Model Predictive  Control by using Additional Weighting Terms,” in Proc. 51st IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2012, pp. 2625–2630.
    148. G. Seyboth, D. V. Dimarogonas, K. H. Johansson, and F. Allgöwer, “Static Diffusive Couplings in Heterogeneous Linear Networks,” in Proc. 3rd IFAC Workshop on Distributed Estimation and Control in  Networked Systems (NecSys), Santa Barbara, CA, USA, 2012, pp. 258–263.
    149. G. Seyboth, G. S. Schmidt, and F. Allgöwer, “Cooperative Control of Linear Parameter-Varying Systems,” in Proc.\ American Control Conf.\ (ACC), Montreal, Canada, 2012, pp. 2407–2412.
    150. S. Waldherr, J. Hasenauer, and F. Allgöwer, “Set based uncertainty analysis and parameter estimation of biological networks with the BioSDP toolbox,” in Proc.\ 9th Int.\ Workshop on Computational Systems Biology (WCSB), Ulm, Germany, 2012.
    151. S. Schuler, D. Zelazo, and F. Allgöwer, “Design of Sparse Relative Sensing Networks,” in Proc.\ 51st IEEE Conf.\ Decision and Control (CDC), Maui, HI, USA, 2012, pp. 2749–2754.
    152. G. Seyboth, G. S. Schmidt, and F. Allgöwer, “Output Synchronization of Linear Parameter-varying Systems via Dynamic Couplings,” in Proc.\ 51st IEEE Conf.\ Decision and Control (CDC), Maui, HI, USA, 2012, pp. 5128–5133.
    153. D. Zelazo and F. Allgöwer, “Eulerian Consensus Networks,” in Proc.\ 51st IEEE Conf.\ Decision and Control (CDC), Maui, HI, USA, 2012, pp. 4715–4720.
    154. D. Schittler, J. Hasenauer, and F. Allgöwer, “A model for proliferating cell populations that accounts for cell types,” in Proc.\ 9th Int.\ Workshop on Computational Systems Biology (WCSB), Ulm, Germany, 2012, pp. 84–87.
    155. B. W. Carabelli et al., “Exact Convex Formulations of Network-Oriented Optimal Operator Placement,” in Proc.\ 51st IEEE Conf.\ Decision and Control (CDC), Maui, HI, USA, 2012, pp. 3777–3782.
    156. M. A. Müller, D. Liberzon, and F. Allgöwer, “Relaxed conditions for norm-controllability of nonlinear systems,” in Proc.\ 51st IEEE Conf.\ Decision and Control (CDC), Maui, HI, USA, 2012, pp. 314–319.
    157. C. Breindl, M. Chaves, J. L. Gouzé, and F. Allgöwer, “Structure estimation for unate Boolean models of gene regulation networks,” in Proc.\ 16th IFAC Symp.\ System Identification (SYSID), Brussels, Belgium, 2012, pp. 1725--1730.
    158. M. Reble, D. E. Quevedo, and F. Allgöwer, “Improved Stability Conditions for Unconstrained Nonlinear Model Predictive Control by using Additional Weighting Terms,” in Proc.\ 51st IEEE Conf.\ Decision and Control (CDC), Maui, HI, USA, 2012, pp. 2625–2630.
    159. G. Seyboth, D. V. Dimarogonas, K. H. Johansson, and F. Allgöwer, “Static Diffusive Couplings in Heterogeneous Linear Networks,” in Proc.\ 3rd IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), Santa Barbara, CA, USA, 2012, pp. 258–263.
    160. R. Blind and F. Allgöwer, “Analysis of Networked Event-Based Control with a Shared Communication  Medium: Part I - Pure ALOHA,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 10092–10097.
    161. R. Blind and F. Allgöwer, “On the Optimal Sending Rate for Networked Control Systems with a  Shared Communication Medium,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 4704–4709.
    162. R. Blind and F. Allgöwer, “Analysis of Networked Event-Based Control with a Shared Communication  Medium: Part II - Slotted ALOHA,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 8830–8835.
    163. P. Weber, J. Hasenauer, F. Allgöwer, and N. Radde, “Parameter estimation and identifiability of biological networks using  relative data,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 11648–11653.
    164. F. Bayer, M. Bürger, M. Guay, and F. Allgöwer, “On State-Constrained Control of a CSTR,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 6079–6084.
    165. M. A. Müller, M. Reble, and F. Allgöwer, “A general distributed MPC framework for cooperative control,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 7987–7992.
    166. B. Briegel, D. Zelazo, M. Bürger, and F. Allgöwer, “On the Zeros of Consensus Networks,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 1890–1895.
    167. J. Hasenauer, S. Waldherr, M. Doszczak, N. Radde, P. Scheurich, and F. Allgöwer, “Parameter estimation and uncertainty analysis for models of heterogeneous  cell populations,” in Proc. 12th Int. Conf. Systems Biology (ICSB), Heidelberg/Mannheim, Germany, 2011.
    168. K. Kashima, A. Papachristodoulou, and F. Allgöwer, “Connection Profile Robustness in a Heterogeneous Network of Piecewise  Affine FitzHugh-Nagumo Models,” in Proc. SICE Annual Conf., Tokyo, Japan, 2011, pp. 2093–2098.
    169. S. Yu, H. Chen, and F. Allgöwer, “Tube MPC scheme based on robust control invariant set with application  to Lipschitz nonlinear systems,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 2650–2655.
    170. J. Hasenauer, K. Erbertseder, M. Doszczak, R. Helmig, P. Scheurich, and F. Allgöwer, “Towards a multi-scale model for the therapeutic action of TRAIL  in lung carcinoma,” in Proc. 12th Int. Conf. Systems Biology (ICSB), Heidelberg/Mannheim, Germany, 2011.
    171. J. Hasenauer, C. Andres, T. Hucho, and F. Allgöwer, “A threshold-free method for assessing the responsiveness of heterogeneous  populations: DRG-neurons as a case study,” in Proc. 8th Int. Workshop on Computational Systems Biology (WCSB), Zürich, Switzerland, 2011, p. 209.
    172. M. Bürger, D. Zelazo, and F. Allgöwer, “Network Clustering: A Dynamical Systems and Saddle-Point Perspective,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 7825–7830.
    173. D. Zelazo, M. Bürger, and F. Allgöwer, “A Distributed Real-Time Algorithm for Preference-Based Agreement,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 8933–8938.
    174. M. Reble and F. Allgöwer, “Unconstrained Nonlinear Model Predictive Control and Suboptimality  Estimates for Continuous-Time Systems,” in Proc. 18th IFAC World Congress, Milan, Italy, 2011, pp. 6733–6738.
    175. J. Hasenauer, J. Heinrich, M. Doszczak, P. Scheurich, D. Weiskopf, and F. Allgöwer, “Visualization methods and support vector machines as tools for determining  markers in models of heterogeneous populations: Proapoptotic signaling  as a case study,” in Proc. 8th Int. Workshop on Computational Systems Biology (WCSB), Zürich, Switzerland, 2011, pp. 61–64.
    176. M. Bürger, G. Notarstefano, F. Allgöwer, and F. Bullo, “A distributed simplex algorithm and the multi-agent assignment problem,” in Proc. American Control Conf. (ACC), San Francisco, CA, USA, 2011, pp. 2639–2644.
    177. M. Reble, M. A. Müller, and F. Allgöwer, “Unconstrained Model Predictive Control and Suboptimality Estimates  for Nonlinear Time-Delay Systems,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 7599–7604.
    178. S. Yu, M. Reble, H. Chen, and F. Allgöwer, “Inherent robustness properties of quasi-infinite horizon NMPC,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 179–184.
    179. C. Böhm, S. Yu, and F. Allgöwer, “Moving horizon $H_ınfty$ control of constrained  periodically time-varying systems,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 10156–10161.
    180. F. Deroo, C. Maier, C. Böhm, and F. Allgöwer, “Offline NMPC for continuous-time systems using sum of squares,” in Proc. American Control Conf. (ACC), San Francisco, CA, USA, 2011, pp. 5163–5168.
    181. M. Reble, D. E. Quevedo, and F. Allgöwer, “Stochastic Stability and Performance Estimates of Packetized Unconstrained  Model Predictive Control for Networked Control Systems,” in Proc. 9th IEEE Int. Conf. Control and Automation, Santiago, Chile, 2011, pp. 171–176.
    182. M. A. Müller, D. Liberzon, and F. Allgöwer, “On norm-controllabilty of nonlinear systems,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 1741–1746.
    183. M. Reble, F. D. Brunner, and F. Allgöwer, “Model Predictive Control for Nonlinear Time-Delay Systems without  Terminal Constraint,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 9254–9259.
    184. C. Breindl, D. Schittler, S. Waldherr, and F. Allgöwer, “Structural requirements and discrimination of cell differentiation  networks,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 11767–11772.
    185. M. Löhning, J. Hasenauer, M. Khammash, and F. Allgöwer, “Optimierung mittels reduzierter Modelle mit garantierter Güte,” in Tagungsband Workshop GMA-Fachausschuss 1.30 ``Modellbildung, Identifikation  und Simulation in der Automatisierungstechnik’’, 2011.
    186. M. Bürger, G. Notarstefano, and F. Allgöwer, “Locally Constrained Decision Making via Two-Stage Distributed Simplex,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 5911–5916.
    187. S. Schuler, M. D. Gruhler, U. Münz, and F. Allgöwer, “Design of Structured Static Output Feedback Controllers,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 271–276.
    188. D. Schittler, J. Hasenauer, and F. Allgöwer, “A generalized population model for cell proliferation: Integrating  division numbers and label dynamics,” in Proc. 8th Int. Workshop on Computational Systems Biology (WCSB), Zürich, Switzerland, 2011, pp. 165–168.
    189. M. Löhning, J. Hasenauer, and F. Allgöwer, “Trajectory-based model reduction of nonlinear biochemical networks  employing the observability normal form,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 10442–10447.
    190. M. Löhning, J. Hasenauer, and F. Allgöwer, “Steady state stability preserving nonlinear model reduction using  sequential convex optimization,” in Proc. 50th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Orlando, FL, USA, 2011, pp. 7158–7163.
    191. M. Kögel, R. Blind, F. Allgöwer, and R. Findeisen, “Optimal and optimal-linear control over lossy, distributed networks,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 13239–13244.
    192. G. S. Schmidt, C. Ebenbauer, and F. Allgöwer, “Observability Properties of the Periodic Toda Lattice,” in Proc. 9th IEEE Int. Conf. Control and Automation, Santiago, Chile, 2011, pp. 704–709.
    193. M. A. Müller and F. Allgöwer, “Model predictive control of switched nonlinear systems under average  dwell-time,” in Proc. American Control Conf. (ACC), San Francisco, CA, USA, 2011, pp. 5169–5174.
    194. S. Schuler, C. Ebenbauer, and F. Allgöwer, “$\ell_0$-System Gain and $\ell_1$-Optimal Control,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 9230–9235.
    195. A. Joos, M. A. Müller, D. Baumgärtner, W. Fichter, and F. Allgöwer, “Nonlinear Predictive Control Based on Time-Domain Simulation for  Automatic Landing,” in Proc. AIAA Guidance, Navigation, and Control Conf., Portland, OR, USA, 2011, vol. 2, pp. 1619–1633.
    196. R. Blind and F. Allgöwer, “Analysis of Networked Event-Based Control with a Shared Communication Medium: Part I - Pure ALOHA,” in Proc.\ 18th IFAC World Congress, Milano, Italy, 2011, pp. 10092–10097.
    197. R. Blind and F. Allgöwer, “On the Optimal Sending Rate for Networked Control Systems with a Shared Communication Medium,” in Proc.\ 50th IEEE Conf.\ Decision and Control (CDC), European Control Conf.\ (ECC), Orlando, FL, USA, 2011, pp. 4704–4709.
    198. R. Blind and F. Allgöwer, “Analysis of Networked Event-Based Control with a Shared Communication Medium: Part II - Slotted ALOHA,” in Proc.\ 18th IFAC World Congress, Milano, Italy, 2011, pp. 8830–8835.
    199. P. Weber, J. Hasenauer, F. Allgöwer, and N. Radde, “Parameter estimation and identifiability of biological networks using  relative data,” in Proc.\ 18th IFAC World Congress, Milano, Italy, 2011, pp. 11648–11653.
    200. M. A. Müller, M. Reble, and F. Allgöwer, “A general distributed MPC framework for cooperative control,” in Proc.\ 18th IFAC World Congress, Milano, Italy, 2011, pp. 7987–7992.
    201. B. Briegel, D. Zelazo, M. Bürger, and F. Allgöwer, “On the Zeros of Consensus Networks,” in Proc.\ 50th IEEE Conf.\ Decision and Control (CDC), European Control Conf.\ (ECC), Orlando, FL, USA, 2011, pp. 1890–1895.
    202. J. Hasenauer, C. Andres, T. Hucho, and F. Allgöwer, “A threshold-free method for assessing the responsiveness of heterogeneous populations: DRG-neurons as a case study,” in Proc.\ 8th Int.\ Workshop on Computational Systems Biology (WCSB), Zürich, Switzerland, 2011, p. 209.
    203. M. Bürger, D. Zelazo, and F. Allgöwer, “Network Clustering: A Dynamical Systems and Saddle-Point Perspective,” in Proc.\ 50th IEEE Conf.\ Decision and Control (CDC), European Control Conf.\ (ECC), Orlando, FL, USA, 2011, pp. 7825–7830.
    204. F. Deroo, C. Maier, C. Böhm, and F. Allgöwer, “Offline NMPC for continuous-time systems using sum of squares,” in Proc.\ American Control Conf.\ (ACC), San Francisco, CA, USA, 2011, pp. 5163--5168.
    205. M. A. Müller, D. Liberzon, and F. Allgöwer, “On norm-controllabilty of nonlinear systems,” in Proc.\ 50th IEEE Conf.\ Decision and Control (CDC), European Control Conf.\ (ECC), Orlando, FL, USA, 2011, pp. 1741–1746.
    206. C. Breindl, D. Schittler, S. Waldherr, and F. Allgöwer, “Structural requirements and discrimination of cell differentiation networks,” in Proc.\ 18th IFAC World Congress, Milano, Italy, 2011, pp. 11767–11772.
    207. D. Schittler, J. Hasenauer, and F. Allgöwer, “A generalized population model for cell proliferation: Integrating division numbers and label dynamics,” in Proc.\ 8th Int.\ Workshop on Computational Systems Biology (WCSB), Zürich, Switzerland, 2011, pp. 165–168.
    208. M. Löhning, J. Hasenauer, and F. Allgöwer, “Trajectory-based model reduction of nonlinear biochemical networks employing the observability normal form,” in Proc.\ 18th IFAC World Congress, Milano, Italy, 2011, pp. 10442–10447.
    209. M. Löhning, J. Hasenauer, and F. Allgöwer, “Steady state stability preserving nonlinear model reduction using sequential convex optimization,” in Proc.\ 50th IEEE Conf.\ Decision and Control (CDC), European Control Conf.\ (ECC), Orlando, FL, USA, 2011, pp. 7158–7163.
    210. M. Kögel, R. Blind, F. Allgöwer, and R. Findeisen, “Optimal and optimal-linear control over lossy, distributed networks,” in Proc.\ 18th IFAC World Congress, Milano, Italy, 2011, pp. 13239–13244.
    211. G. S. Schmidt, C. Ebenbauer, and F. Allgöwer, “Observability Properties of the Periodic Toda Lattice,” in Proc.\ 9th IEEE Int.\ Conf.\ Control and Automation, Santiago, Chile, 2011, pp. 704–709.
    212. M. A. Müller and F. Allgöwer, “Model predictive control of switched nonlinear systems under average dwell-time,” in Proc.\ American Control Conf.\ (ACC), San Francisco, CA, USA, 2011, pp. 5169–5174.
    213. S. Schuler, W. Zhou, U. Münz, and F. Allgöwer, “Controller Structure Design for Decentralized Control of Higher Order  Subsystems,” in Proc. 2nd IFAC Workshop on Estimation and Control of Networked Systems  (NecSys), Annecy, France, 2010, pp. 296--274.
    214. G. S. Schmidt, C. Ebenbauer, and F. Allgöwer, “Synchronization Conditions for Lyapunov Oscillators,” in Proc. 49th IEEE Conf. Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 6230--6235.
    215. C. Böhm and F. Allgöwer, “Efficient offline model predictive control of constrained nonlinear  periodic systems,” in Proc. IFAC Workshop on Periodic Control Systems (PSYCO), Antalya, Turkey, 2010.
    216. A. Freuer, M. Reble, C. Böhm, and F. Allgöwer, “Efficient Model Predictive Control for Linear Periodic Systems,” in Proc. 19th Int. Symp. Mathematical Theory of Networks and Systems  (MTNS), Budapest, Hungary, 2010, pp. 1403–1409.
    217. A. Kramer, J. Hasenauer, F. Allgöwer, and N. Radde, “Computation of the posterior entropy in a Bayesian framework for  parameter estimation in biological networks,” in Proc. IEEE Int. Conf. Control Applications (CCA), Yokohama, Japan, 2010, pp. 493–498.
    218. C. Böhm, M. Lazar, and F. Allgöwer, “A relaxation of Lyapunov conditions and controller synthesis for  discrete-time periodic systems,” in Proc. 49th IEEE Conf. Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 3277--3282.
    219. M. Reble and F. Allgöwer, “Stabilizing design parameters for model predictive control of constrained  nonlinear time-delay systems,” in Proc. 9th IFAC Workshop on Time Delay Systems, Prague, Czech Republic, 2010.
    220. S. Waldherr, F. Allgöwer, and N. Radde, “Generic bifurcations in the dynamics of biochemical networks,” in Proc. IEEE Int. Conf. Control Applications (CCA), Yokohama, Japan, 2010, pp. 135--141.
    221. C. Breindl, S. Waldherr, and F. Allgöwer, “A robustness measure for the stationary behavior of qualitative gene  regulation networks,” in Proc. 11th Symp. Comput. Appl. Biotechnol. (CAB), Leuven, Belgium, 2010, pp. 36–41.
    222. D. Schlipf, S. Schuler, P. Grau, F. Allgöwer, and M. Kühn, “Look-Ahead Cyclic Pitch Control Using LIDAR,” in Proc. of the Science of Making Torque from Wind (TORQUE), 2010.
    223. P. Wieland, G. S. Schmidt, R. Sepulchre, and F. Allgöwer, “Phase Synchronization through Entrainment by a Consensus Input,” in Proc. 49th IEEE Conf. Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 535--539.
    224. M. Reble and F. Allgöwer, “General Design Parameters of Model Predictive Control for Nonlinear  Time-Delay Systems,” in Proc. 49th IEEE Conf. Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 176--181.
    225. S. Schuler, D. Schlipf, M. Kühn, and F. Allgöwer, “$\ell_1$-Optimal Multivariable Pitch Control for Load Reduction  on Large Wind Turbines,” in Proc. Scientific Track at the European Wind Energy Conf. (EWEC), Warsaw, Poland, 2010, pp. 110–112.
    226. S. Yu, C. Böhm, H. Chen, and F. Allgöwer, “Robust model predictive control with disturbance invariant sets,” in Proc. American Control Conf. (ACC), Baltimore, MD, USA, 2010, pp. 6262--6267.
    227. G. S. Schmidt, J. Wu, U. Münz, and F. Allgöwer, “Consensus in Bistable and Multistable Multi-Agent Systems,” in Proc. 49th IEEE Conf. Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 7135–7140.
    228. J. Hasenauer, C. Breindl, S. Waldherr, and F. Allgöwer, “Approximative classification of regions in parameter spaces of nonlinear  ODEs yielding different qualitative behavior,” in Proc. 49th IEEE Conf. Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 4114–4119.
    229. P. Wieland and F. Allgöwer, “On consensus among identical linear systems using input-decoupled  functional observers,” in Proc. American Control Conf. (ACC), Baltimore, MD, USA, 2010, pp. 1641–1646.
    230. C. Böhm, M. Lazar, and F. Allgöwer, “Stability analysis of periodically time-varying systems using periodic  Lyapunov functions,” in Proc. IFAC Workshop on Periodic Control Systems (PSYCO), Antalya, Turkey, 2010.
    231. J. Hasenauer, S. Waldherr, M. Doszczak, P. Scheurich, and F. Allgöwer, “Density-based modeling and identification of biochemical networks  in cell populations,” in Proc. 9th IFAC Symp. Dynamics and Control of Process Systems (DYCOPS), Leuven, Belgium, 2010, pp. 320–325.
    232. G. Goebel, U. Münz, and F. Allgöwer, “Stabilization of linear systems with distributed input delay,” in Proc. American Control Conf. (ACC), Baltimore, Maryland, USA, 2010, pp. 5800--5806.
    233. C. Maier, C. Böhm, F. Deroo, and F. Allgöwer, “Predictive control for polynomial systems subject to constraints  using sum of squares,” in Proc. 49th IEEE Conf. Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 3433--3438.
    234. M. Bürger, G. S. Schmidt, and F. Allgöwer, “Preference Based Group Agreement in Cooperative Control,” in Proc. 8th IFAC Symp. Nonlinear Control Systems (NOLCOS), Bologna, Italy, 2010, pp. 149–154.
    235. J. Hasenauer et al., “Single-cells vs. cell populations - From a binary decision to a continuous  response,” in Proc. Conf. Systems Biology of Mammalian Cells (SBMC), Freiburg, Germany, 2010.
    236. O. Ajala, S. Schuler, and F. Allgöwer, “$\ell_ınfty$-Gain Controller Order Reduction for Discrete-Time  Systems,” in Proc. American Control Conf. (ACC), Baltimore, MD, USA, 2010, pp. 329–334.
    237. M. Kögel, R. Blind, and F. Allgöwer, “Optimal Control Over Unreliable Networks with Uncertain Loss Rates,” in Proc. American Control Conf. (ACC), Baltimore, MD, USA, 2010, pp. 3672–3677.
    238. S. Schuler, U. Münz, and F. Allgöwer, “Optimal Controller Structure Reduction for Decentralized Control,” in Proc. 4th IFAC Symp. System, Structure and Control (SSSC), Ancona, Italy, 2010, pp. 303–308.
    239. S. Yu, C. Böhm, H. Chen, and F. Allgöwer, “MPC with one free control action for constrained LPV systems,” in Proc. IEEE Int. Conf. Control Applications (CCA), Yokohama, Japan, 2010, pp. 1343–1348.
    240. A. Kramer, J. Hasenauer, F. Allgöwer, and N. Radde, “Computation of the posterior entropy in a Bayesian framework for parameter estimation in biological networks,” in Proc.\ IEEE Int.\ Conf.\ Control Applications (CCA), Yokohama, Japan, 2010, pp. 493–498.
    241. M. Reble and F. Allgöwer, “General Design Parameters of Model Predictive Control for Nonlinear Time-Delay Systems,” in Proc.\ 49th IEEE Conf.\ Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 176--181.
    242. G. S. Schmidt, J. Wu, U. Münz, and F. Allgöwer, “Consensus in Bistable and Multistable Multi-Agent Systems,” in Proc.\ 49th IEEE Conf.\ Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 7135–7140.
    243. P. Wieland and F. Allgöwer, “On consensus among identical linear systems using input-decoupled functional observers,” in Proc.\ American Control Conf.\ (ACC), Baltimore, MD, USA, 2010, pp. 1641–1646.
    244. G. Goebel, U. Münz, and F. Allgöwer, “Stabilization of linear systems with distributed input delay,” in Proc.\  American Control Conf.\ (ACC), Baltimore, Maryland, USA, 2010, pp. 5800--5806.
    245. S. Schuler, U. Münz, and F. Allgöwer, “Optimal Controller Structure Reduction for Decentralized Control,” in Proc.\ 4th IFAC Symp.\ System, Structure and Control (SSSC), Ancona, Italy, 2010, pp. 303–308.
    246. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Output Consensus Controller Design for Nonlinear Relative Degree  One Multi-Agent Systems with Delays,” in Proc. 8th IFAC Workshop on Time Delay Systems, Sinaia, Romania, 2009, pp. 370–375.
    247. S. Yu, C. Böhm, H. Chen, and F. Allgöwer, “Moving horizon $\ell_2$ control of LPV systems subject to constraints,” in Proc. 14th Int. Conf. Methods and Models in Automation and Robotics, Miedzyzdroje, Poland, 2009, pp. 354–359.
    248. R. Blind and F. Allgöwer, “Estimating the Fates of the Control Packets for Networked Control  Systems with Loss of Control and Measurement Packets,” in Proc. 48th IEEE Conf. Decision and Control (CDC), 28th Chinese Control  Conf. (CCC), Shanghai, China, 2009, pp. 2687–1692.
    249. M. A. Müller, S. Waldherr, and F. Allgöwer, “The transcritical bifurcation in absolutely stable feedback systems,” in Proc. European Control Conf. (ECC), Budapest, Hungary, 2009, pp. 2146--2151.
    250. C. Maier and F. Allgöwer, “A Set-Valued Filter for Discrete Time Polynomial Systems using Sum  of Squares Programming,” in Proc. 48th IEEE Conf. Decision and Control (CDC), Shanghai, China, 2009, pp. 223--228.
    251. S. Schuler and F. Allgöwer, “$\ell_ınfty$-Gain Model Reduction for Discrete Time Systems  via LMIs,” in Proc. American Control Conf. (ACC), St. Louis, MO, USA, 2009, pp. 5701–5706.
    252. S. Waldherr, J. Hasenauer, and F. Allgöwer, “Estimation of biochemical network parameter distributions in cell  populations,” in Proc. 15th IFAC Symp. System Identification (SYSID), Brussels, Belgium, 2009, pp. 1265--1270.
    253. M. Reble and F. Allgöwer, “Modellprädiktive Regelung für nichtlineare Totzeitsysteme,” in Tagungsband Workshop GMA-Fachausschuss 1.40 ``Theoretische Verfahren  der Regelungstechnik’’, 2009.
    254. S. Yu, C. Böhm, H. Chen, and F. Allgöwer, “Stabilizing model predictive control for LPV systems subject to  constraints with parameter-dependent control law,” in Proc. American Control Conf. (ACC), St. Louis, 2009, pp. 3118--3123.
    255. S. Maldonado, F. Allgöwer, and R. Findeisen, “Global Sensitivity Analysis of Force-induced Bone Growth and Adaptation  using Semidefinite Programming,” in Proc. 3rd Foundations of Systems Biology in Engineering (FOSBE), Denver, CO, USA, 2009, pp. 141–144.
    256. U. Münz, C. Böhm, J. Eck, M. Reble, P. Schumm, and F. Allgöwer, “A Matlab-Based Game for Advanced Automatic Control Education,” in Proc. 8th IFAC Symp. Advances in Control Education, Kumamoto, Japan, 2009, pp. 140–145.
    257. R. Blind and F. Allgöwer, “A controller design for Networked Control Systems with random delays  via the Jump Linear System approach, which reduces the effects of  the delay,” in Proc. European Control Conf. (ECC), Budapest, Hungary, 2009, pp. 1728–1733.
    258. S. Waldherr, F. Allgöwer, and E. W. Jacobsen, “Kinetic perturbations as robustness analysis tool for biochemical  reaction networks,” in Proc. 48th IEEE Conf. Decision and Control (CDC), Shanghai, China, 2009, pp. 4572--4577.
    259. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Generalized Nyquist Consensus Condition for Linear Multi-Agent  Systems with Heterogeneous Delays,” in Proc. 1st IFAC Workshop on Estimation and Control of Networked Systems  (NecSys), Venice, Italy, 2009, pp. 24–29.
    260. T. Haag, U. Münz, and F. Allgöwer, “Comparison of Different Stability Conditions for Linear Time-Delay  Systems with Incommensurate Delays,” in Proc. 8th IFAC Workshop on Time Delay Systems, Sinaia, Romania, 2009, pp. 136–141.
    261. M. Reble, C. Böhm, and F. Allgöwer, “Nonlinear Model Predictive Control for Periodic Systems using LMIs,” in Proc. European Control Conf. (ECC), Budapest, Hungary, 2009, pp. 3365–3370.
    262. C. Böhm, S. Yu, and F. Allgöwer, “Predictive control for constrained discrete-time periodic systems  using a time-varying terminal region,” in Proc. 14th Int. Conf. Methods and Models in Automation and Robotics, Miedzyzdroje, Poland, 2009.
    263. C. Breindl and F. Allgöwer, “Verification of multistability in gene regulation networks: A combinatorial  approach,” in Proc. 48th IEEE Conf. Decision and Control (CDC), Shanghai, China, 2009, pp. 5637–5642.
    264. R. Blind, S. Uhlich, B. Yang, and F. Allgöwer, “Robustification and Optimization of a Kalman Filter with Measurement  Loss using Linear Precoding,” in Proc. American Control Conf. (ACC), St. Louis, MO, USA, 2009, pp. 2222–2227.
    265. R. M. Esfanjani, M. Reble, U. Münz, S. K. Y. Nikravesh, and F. Allgöwer, “Model Predictive Control of Constrained Nonlinear Time-Delay Systems,” in Proc. 48th IEEE Conf. Decision and Control (CDC), Shanghai, China, 2009, pp. 1324–1329.
    266. J. Hasenauer, P. Rumschinski, S. Waldherr, S. Borchers, F. Allgöwer, and R. Findeisen, “Guaranteed steady-state bounds for uncertain chemical processes,” in Proc. IFAC Int. Symp. Advanced Control of Chemical Processes (ADCHEM), 2009, pp. 674–679.
    267. C. Böhm, S. Yu, R. Findeisen, and F. Allgöwer, “Predictive control for Lure systems subject to constraints using  LMIs,” in Proc. European Control Conf. (ECC), Budapest, Hungary, 2009, pp. 3389--3394.
    268. P. Wieland and F. Allgöwer, “An Internal Model Principle for Consensus in Heterogeneous Linear  Multi-Agent Systems,” in Proc. 1st IFAC Workshop on Estimation and Control of Networked Systems  (NecSys), Venice, Italy, 2009, pp. 7–12.
    269. G. S. Schmidt, U. Münz, and F. Allgöwer, “Multi-Agent Speed Consensus via Delayed Position Feedback with Application  to Kuramoto Oscillators,” in Proc. European Control Conf. (ECC), Budapest, Hungary, 2009, pp. 2464–2469.
    270. C. Breindl, S. Waldherr, A. Hausser, and F. Allgöwer, “Modeling cofilin mediated regulation of cell migration as a biochemical  two-input switch,” in Proc. 3rd Foundations of Systems Biology in Engineering (FOSBE), 2009, pp. 60–63.
    271. P. Wieland and F. Allgöwer, “An Internal Model Principle for Synchronization,” in Proc. 7th IEEE Int. Conf. Control and Automation, Christchurch, New Zealand, 2009, pp. 285–290.
    272. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Generalized Nyquist Consensus Condition for Large High-Order Linear  Multi-Agent Systems with Communication Delays,” in Proc. 48th IEEE Conf. Decision and Control (CDC), Shanghai, China, 2009, pp. 4765–4771.
    273. S. Yu, C. Böhm, H. Chen, and F. Allgöwer, “Moving horizon $\ell_2$ control of LPV systems subject to constraints,” in Proc.\ 14th Int.\ Conf.\ Methods and Models in Automation and Robotics, Miedzyzdroje, Poland, 2009, pp. 354–359.
    274. J. Hasenauer, S. Waldherr, and F. Allgöwer, “Estimation of biochemical network parameter distributions in cell populations,” in Workshop on Cancer Systems Biology, Rostock, Germany, 2009.
    275. S. Yu, C. Böhm, H. Chen, and F. Allgöwer, “Stabilizing model predictive control for LPV systems subject to constraints with parameter-dependent control law,” in Proc.\ American Control Conf.\ (ACC), St. Louis, 2009, pp. 3118--3123.
    276. U. Münz, C. Böhm, J. Eck, M. Reble, P. Schumm, and F. Allgöwer, “A Matlab-Based Game for Advanced Automatic Control Education,” in Proc.\ 8th IFAC Symp.\ Advances in Control Education, Kumamoto, Japan, 2009, pp. 140–145.
    277. C. Böhm, S. Yu, and F. Allgöwer, “Predictive control for constrained discrete-time periodic systems using a time-varying terminal region,” in Proc.\ 14th Int.\ Conf.\ Methods and Models in Automation and Robotics, Miedzyzdroje, Poland, 2009.
    278. R. Blind, S. Uhlich, B. Yang, and F. Allgöwer, “Robustification and Optimization of a Kalman Filter with Measurement Loss using Linear Precoding,” in Proc.\ American Control Conf.\ (ACC), St. Louis, MO, USA, 2009, pp. 2222–2227.
    279. J. Hasenauer, P. Rumschinski, S. Waldherr, S. Borchers, F. Allgöwer, and R. Findeisen, “Guaranteed steady-state bounds for uncertain chemical processes,” in Proc.\ IFAC Int.\ Symp.\ Advanced Control of Chemical Processes (ADCHEM), 2009, pp. 674–679.
    280. C. Böhm, S. Yu, R. Findeisen, and F. Allgöwer, “Predictive control for Lure systems subject to constraints using LMIs,” in Proc.\ European Control Conf.\ (ECC), Budapest, Hungary, 2009, pp. 3389--3394.
    281. C. Breindl, S. Waldherr, A. Hausser, and F. Allgöwer, “Modeling cofilin mediated regulation of cell migration as a biochemical two-input switch,” in Proc.\ 3rd Foundations of Systems Biology in Engineering (FOSBE), 2009, pp. 60–63.
    282. U. Münz, P. Schumm, and F. Allgöwer, “Educational Games in Control,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 12625–12630.
    283. D. Geffen, R. Findeisen, M. Schliemann, F. Allgöwer, and M. Guay, “Observability based parameter identifiability for biochemical reaction  networks,” in Proc. American Control Conf. (ACC), Seattle, WA, USA, 2008, pp. 2130–2135.
    284. M. Bürger, T. Raff, C. Ebenbauer, and F. Allgöwer, “Extensions on a Certainty-Equivalence Feedback Design with a Class  of Feedbacks Which Guarantee ISS,” in Proc. American Control Conf. (ACC), Seattle, WA, USA, 2008, pp. 383–388.
    285. J. Maess, J. Becker, L. Gaul, and F. Allgöwer, “Two-Degree-of-Freedom Tracking Control of Piezoelectric Tube Scanners  in Two-Dimensional Scanning Applications,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 8257–8262.
    286. T. Raff, D. Sinz, and F. Allgöwer, “Model Predictive Control of Uncertain Continuous-Time Systems with  Piecewise Constant Control Input: A Convex Approach,” in Proc. American Control Conf. (ACC), Seattle, WA, USA, 2008, pp. 1109–1114.
    287. J. K. Johnsen, F. Dörfler, and F. Allgöwer, “$L_2$-gain of Port-Hamiltonian systems and application  to a biochemical fermenter model,” in Proc. American Control Conf. (ACC), Seattle, USA, 2008, pp. 153–158.
    288. P. Wieland, J.-S. Kim, H. Scheu, and F. Allgöwer, “On consensus in multi-agent systems with linear high-order agents,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 1541–1546.
    289. C. Böhm, T. Raff, R. Findeisen, and F. Allgöwer, “Calculating the terminal region of NMPC for Lure systems,” in Proc. American Control Conf. (ACC), Seattle, WA, USA, 2008, pp. 1127--1132.
    290. S. Waldherr, T. Eißing, and F. Allgöwer, “Analysis of Feedback Mechanisms in Cell-biological Systems,” in Proc. of the 17th IFAC World Congress, Seoul, Korea, 2008, pp. 15861--15866.
    291. S. Yu, H. Chen, C. Böhm, and F. Allgöwer, “Moving horizon $H_ınfty$ control based on T-S models,” in Proc. Int. Workshop on Assessment and Future Directions of Nonlinear  Model Predictive Control, Pavia, Italy, 2008.
    292. T. Raff, M. Kögel, and F. Allgöwer, “Observer with Sample-and-Hold Updating for Lipschitz Nonlinear Systems  with Nonuniformly Sampled Measurements,” in Proc. American Control Conf. (ACC), Seattle, WA, USA, 2008, pp. 5254–5257.
    293. S. Waldherr, R. Findeisen, and F. Allgöwer, “Global Sensitivity Analysis of Biochemical Reaction Networks via  Semidefinite Programming,” in Proc. of the 17th IFAC World Congress, Seoul, Korea, 2008, pp. 9701–9706.
    294. U. Münz, J. M. Rieber, and F. Allgöwer, “Robust stability of Distributed Delay Systems,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 12354–12358.
    295. S. Waldherr, M. Doszczak, M. Schliemann, J. Schreiner, P. Scheurich, and F. Allgöwer, “The TNF Receptor Signalling Network: Modular Modelling and Cell-type  Specific Analysis,” in 2nd Conference on Systems Biology of the Mammalian Cell, Dresden, 2008.
    296. J. Hasenauer, S. Waldherr, and F. Allgöwer, “Global sensitivity analysis of biochemical reaction networks using  semidefinite programming,” in Proc. 9th Int. Conf. Systems Biology (ICSB), Gothenburg, Sweden, 2008.
    297. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Delay-Dependent Rendezvous and Flocking of Large Scale Multi-Agent  Systems with Communication Delays,” in Proc. 47th IEEE Conf. Decision and Control (CDC), Cancun, Mexico, 2008, pp. 2038–2043.
    298. N. Dmitruk, R. Findeisen, and F. Allgöwer, “Optimal measurement feedback control of finite-time continous linear  systems,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 15339–15344.
    299. T. Raff and F. Allgöwer, “An Observer that Converges in Finite Time Due to Measurement-based  State Updates,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 2693–2695.
    300. J. Maess, A. J. Fleming, and F. Allgöwer, “Model-Based Vibration Suppression in Piezoelectric Tube Scanners  through Induced Voltage Feedback,” in Proc. American Control Conf. (ACC), Seattle, WA, USA, 2008, pp. 2022–2027.
    301. S. Waldherr, J. Hasenauer, and F. Allgöwer, “Global sensitivity analysis of uncertain biochemical reaction networks,” in 2nd Int. Work. Syst. Biol., 2008.
    302. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Nonlinear Multi-Agent System Consensus with Time-Varying Delays,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 1522–1527.
    303. C. Böhm, R. Findeisen, and F. Allgöwer, “Avoidance of poorly observable trajectories: A predictive control  perspective,” in Proc. 17th IFAC World Congress, Seoul, Korea, 2008, pp. 1952--1957.
    304. U. Münz, P. Schumm, and F. Allgöwer, “Educational Games in Control,” in Proc.\ 17th IFAC World Congress, Seoul, Korea, 2008, pp. 12625–12630.
    305. D. Geffen, R. Findeisen, M. Schliemann, F. Allgöwer, and M. Guay, “Observability based parameter identifiability for biochemical reaction networks,” in Proc.\ American Control Conf.\ (ACC), Seattle, WA, USA, 2008, pp. 2130–2135.
    306. P. Wieland, J.-S. Kim, H. Scheu, and F. Allgöwer, “On consensus in multi-agent systems with linear high-order agents,” in Proc.\ 17th IFAC World Congress, Seoul, Korea, 2008, pp. 1541–1546.
    307. C. Böhm, T. Raff, R. Findeisen, and F. Allgöwer, “Calculating the terminal region of NMPC for Lure systems,” in Proc.\ American Control Conf.\ (ACC), Seattle, WA, USA, 2008, pp. 1127--1132.
    308. S. Waldherr, T. Eißing, and F. Allgöwer, “Analysis of Feedback Mechanisms in Cell-biological Systems,” in Proc.\ of the 17th IFAC World Congress, Seoul, Korea, 2008, pp. 15861--15866.
    309. J. Hasenauer, S. Waldherr, and F. Allgöwer, “Global sensitivity analysis of biochemical reaction networks using semidefinite programming,” in Proc.\ 9th Int.\ Conf.\ Systems Biology (ICSB), Gothenburg, Sweden, 2008.
    310. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Delay-Dependent Rendezvous and Flocking of Large Scale Multi-Agent Systems with Communication Delays,” in Proc.\ 47th IEEE Conf.\ Decision and Control (CDC), Cancun, Mexico, 2008, pp. 2038–2043.
    311. T. Raff and F. Allgöwer, “An Observer that Converges in Finite Time Due to Measurement-based State Updates,” in Proc.\ 17th IFAC World Congress, Seoul, Korea, 2008, pp. 2693–2695.
    312. J. Maess, A. J. Fleming, and F. Allgöwer, “Model-Based Vibration Suppression in Piezoelectric Tube Scanners through Induced Voltage Feedback,” in Proc.\ American Control Conf.\ (ACC), Seattle, WA, USA, 2008, pp. 2022–2027.
    313. S. Waldherr, J. Hasenauer, and F. Allgöwer, “Global sensitivity analysis of uncertain biochemical reaction networks,” in 2nd Int. Work. Syst. Biol., 2008.
    314. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Nonlinear Multi-Agent System Consensus with Time-Varying Delays,” in Proc.\ 17th IFAC World Congress, Seoul, Korea, 2008, pp. 1522–1527.
    315. S. Waldherr and F. Allgöwer, “A feedback approach to bifurcation analysis in biochemical networks  with many parameters,” in Proc. 2nd Foundations of Systems Biology in Engineering (FOSBE), Stuttgart, Germany, 2007, pp. 479--484.
    316. J. Maess and F. Allgöwer, “Closed-Loop Simulation of Kelvin Probe Force Microscopy based on  Reduced Finite Element Cantilever Modeling,” in 3rd International IEEE Scientific Conference on Physics and Control, Potsdam, Germany, 2007.
    317. U. Münz, C. Ebenbauer, and F. Allgöwer, “Stability of Networked Systems with Multiple Delays Using Linear  Programming,” in Proc. American Control Conf. (ACC), New York City, NY, USA, 2007, pp. 5515--5520.
    318. R. Findeisen, J. Sjoberg, and F. Allgöwer, “Model predictive control of continuous time nonlinear differential  algebraic systems,” in Proc. 7th IFAC Symp. Nonlinear Control Systems (NOLCOS), Pretoria, South Africa, 2007, pp. 165–171.
    319. U. Münz, A. Papachristodoulou, and F. Allgöwer, “Multi-Agent System Consensus in Packet-Switched Networks,” in Proc. European Control Conf. (ECC), Kos, Greece, 2007, pp. 4598--4603.
    320. D. Geffen, R. Findeisen, M. Schliemann, F. Allgöwer, and M. Guay, “The question of parameter identifiability for biochemical reaction  networks considering the NF-$\kappa$B signal transduction pathway,” in Proc. 2nd Foundations of Systems Biology in Engineering (FOSBE), Stuttgart, Germany, 2007, pp. 509–514.
    321. P. Wieland and F. Allgöwer, “Constructive Safety using Control Barrier Functions,” in Proc. 7th IFAC Symp. Nonlinear Control Systems (NOLCOS), Pretoria, South Africa, 2007, pp. 473--478.
    322. J.-S. Kim and F. Allgöwer, “Nonlinear Observer-based Synchronization of Neuron Models,” in 3rd International IEEE Scientific Conference on Physics and Control, Potsdam, Germany, 2007.
    323. S. Waldherr, T. Eißing, and F. Allgöwer, “Analysing biological feedback with tools from control theory,” in FEBS Advanced Lecture Course on Systems Biology, 2007.
    324. T. Raff, C. Angrick, R. Findeisen, J.-S. Kim, and F. Allgöwer, “Model Predictive Control for Nonlinear Time-Delay Systems,” in Proc. 7th IFAC Symp. Nonlinear Control Systems (NOLCOS), Pretoria, South Africa, 2007, pp. 134–139.
    325. A. Schöllig, U. Münz, and F. Allgöwer, “Topology-Dependent Stability of a Network of Dynamical Systems with  Communication Delays,” in Proc. European Control Conf. (ECC), Kos, Greece, 2007, pp. 1197--1202.
    326. T. Raff and F. Allgöwer, “Observers with Impulsive Dynamical Behavior for Linear and Nonlinear  Continuous-Time Systems,” in Proc. 46th IEEE Conf. Decision and Control (CDC), New Orleans, LA, USA, 2007, pp. 4287–4292.
    327. M. Reble, U. Münz, and F. Allgöwer, “Diagnosis of Parametric Faults in Multivariable Nonlinear Systems,” in Proc. 46th IEEE Conf. Decision and Control (CDC), New Orleans, LA, USA, 2007, pp. 366–371.
    328. R. Blind, U. Münz, and F. Allgöwer, “Almost Sure Stability and Transient Behavior of Stochastic Nonlinear  Jump Systems Motivated by Networked Control Systems,” in Proc. 46th IEEE Conf. Decision and Control (CDC), New Orleans, LA, USA, 2007, pp. 3327–3332.
    329. P. Wieland, C. Ebenbauer, and F. Allgöwer, “Ensuring Task-Independent Safety for Multi-Agent Systems by Feedback,” in Proc. American Control Conf. (ACC), New York City, NY, USA, 2007, pp. 3880–3885.
    330. T. Raff and F. Allgöwer, “An Impulsive Observer that Estimates the Exact State of a Linear  Continuous-Time System in Predetermined Finite Time,” in Proc. 12th Mediterranean Conf. Control and Automation (MED), Athens, Greece, 2007.
    331. R. Findeisen, T. Raff, and F. Allgöwer, “Sampled-Data Nonlinear Model Predictive Control for Constrained Continuous  Time Systems,” in Advanced Strategies in Control Systems with Input and Output Constraints, 2007, vol. 346, pp. 207–235.
    332. U. Münz and F. Allgöwer, “$L_2$-Gain Based Controller Design for Linear Systems  with Distributed Delays and Rational Delay Kernels,” in Proc. 7th IFAC Symp. Time-Delay Systems, Nantes, France, 2007.
    333. T. Raff and F. Allgöwer, “Observer Design via Absolute Stability for a Class of Nonlinear Descriptor  Systems,” in Proc. 7th IFAC Symp. Nonlinear Control Systems (NOLCOS), Pretoria, South Africa, 2007, pp. 307–312.
    334. J.-S. Kim and F. Allgöwer, “A nonlinear synchronization scheme for polynomial systems,” in Proc. American Control Conf. (ACC), New York City, NY, USA, 2007, pp. 2588–2593.
    335. S. Waldherr, T. Eißing, M. Chaves, and F. Allgöwer, “Bistability preserving model reduction in apoptosis,” in Proc. 10th Int. IFAC Symp. Computer Appications in Biotechnology, Cancun, Mexico, 2007, pp. 327--332.
    336. J. Maess, A. J. Fleming, and F. Allgöwer, “Simulation of Piezoelectric Tube Actuators by Reduced Finite Element  Models for Controller Design,” in Proc. American Control Conf. (ACC), New York City, NY, USA, 2007, pp. 4221–4226.
    337. S. Waldherr and F. Allgöwer, “A feedback approach to bifurcation analysis in biochemical networks with many parameters,” in Proc.\ 2nd Foundations of Systems Biology in Engineering (FOSBE), Stuttgart, Germany, 2007, pp. 479--484.
    338. P. Wieland and F. Allgöwer, “Constructive Safety using Control Barrier Functions,” in Proc.\ 7th IFAC Symp.\ Nonlinear Control Systems (NOLCOS), Pretoria, South Africa, 2007, pp. 473--478.
    339. J.-S. Kim and F. Allgöwer, “Nonlinear Observer-based Synchronization of Neuron Models,” in 3rd International IEEE Scientific Conference on Physics and Control, Potsdam, Germany, 2007.
    340. S. Waldherr, T. Eißing, and F. Allgöwer, “Analysing biological feedback with tools from control theory,” in FEBS Advanced Lecture Course on Systems Biology, 2007.
    341. T. Raff and F. Allgöwer, “Observers with Impulsive Dynamical Behavior for Linear and Nonlinear Continuous-Time Systems,” in Proc.\ 46th IEEE Conf.\ Decision and Control (CDC), New Orleans, LA, USA, 2007, pp. 4287–4292.
    342. R. Findeisen, T. Raff, and F. Allgöwer, “Sampled-Data Nonlinear Model Predictive Control for Constrained Continuous Time Systems,” in Advanced Strategies in Control Systems with Input and Output Constraints, 2007, vol. 346, pp. 207–235.
    343. U. Münz and F. Allgöwer, “$L_2$-Gain Based Controller Design for Linear Systems with Distributed Delays and Rational Delay Kernels,” in Proc.\ 7th IFAC Symp.\ Time-Delay Systems, Nantes, France, 2007.
    344. S. Waldherr, T. Eißing, M. Chaves, and F. Allgöwer, “Bistability preserving model reduction in apoptosis,” in Proc.\ 10th Int.\ IFAC Symp.\ Computer Appications in Biotechnology, Cancun, Mexico, 2007, pp. 327--332.
    345. T. Raff, S. Huber, Z. K. Nagy, and F. Allgöwer, “Nonlinear Model Predictive Control of a Four Tank System: An Experimental  Stability Study,” in Proc. IEEE Int. Conf. Control Applications (CCA), Munich, Germany, 2006, pp. 237–242.
    346. J. Aßfalg and F. Allgöwer, “Fault diagnosis of constrained nonlinear systems using structured  augmented state models,” in Proc. IFAC SAFEPROCESS, Beijing, China, 2006, pp. 1375–1380.
    347. M. Farina, R. Findeisen, E. Bullinger, S. Bittanti, F. Allgöwer, and P. Wellstead, “Results towards Identifiability Properties of Biochemical Reaction  Networks,” in Proc. 45th IEEE Conf. Decision and Control (CDC), San Diego, CA, USA, 2006, pp. 2104–2109.
    348. S. Waldherr and F. Allgöwer, “Hopf bifurcations and feedback gain in signaling pathways,” in Conference on Systems Biology of Mammalian Cells, Heidelberg, Germany, 2006.
    349. J. M. Rieber, C. W. Scherer, and F. Allgöwer, “Robust $\ell_1$ performance analysis in face of parametric uncertainties,” in Proc. 45th IEEE Conf. Decision and Control (CDC), San Diego, CA, USA, 2006, pp. 5826--5831.
    350. S. Maldonado, S. Borchers, R. Findeisen, and F. Allgöwer, “Modeling bone adaptation and remodeling initiated by mechanical stimuli,” in Proc. Int. Mediterranean Modelling Conf., 2nd European Modeling and  Simulation Symp. (EMSS), Barcelona, Spain, 2006, pp. 403--409.
    351. J. Aßfalg and F. Allgöwer, “Fault diagnosis with structured augmented state models: Modeling,  analysis, and design,” in Proc. 45th IEEE Conf. Decision and Control (CDC), San Diego, CA, USA, 2006, pp. 1165–1170.
    352. T. Raff and F. Allgöwer, “An EKF-based Observer for Nonlinear Time-Delay Systems,” in Proc. American Control Conf. (ACC), Minneapolis, MN, USA, 2006, pp. 3130–3133.
    353. S. Waldherr, T. Eißing, M. Chaves, and F. Allgöwer, “Preservation of bistability in the reduction of an apoptosis model,” in Genomes To Systems Conference, Manchester, UK, 2006.
    354. R. Lepore, A. Vande Wouwer, M. Remy, R. Findeisen, Z. K. Nagy, and F. Allgöwer, “Scheduled optimization of an MMA polymerization process,” in Proc. IFAC Int. Symp. Advanced Control of Chemical Processes (ADCHEM), Gramado, Brazil, 2006, pp. 695--703.
    355. M. Herceg, T. Raff, R. Findeisen, and F. Allgöwer, “Nonlinear Model Predictive Control of a Turbocharged Diesel Engine,” in Proc. IEEE Int. Conf. Control Applications (CCA), Munich, Germany, 2006, pp. 2766–2771.
    356. M. Chaves, T. Eißing, and F. Allgöwer, “Identifying mechanisms for bistability in an apoptosis network,” in Réseaux d’Interactions: Analyse, Modélisation et Simulation  (RIAMS’06), Lyon, France, 2006.
    357. J. M. Rieber, C. W. Scherer, and F. Allgöwer, “On complexity issues in multiobjective controller design using  convex optimization,” in Proc. 5th IFAC Symp. Robust Control Design, Toulouse, France, 2006.
    358. S. Maldonado, S. Borchers, R. Findeisen, and F. Allgöwer, “Mathematical Modeling and Analysis of Force Induced Bone Growth,” in Proc. 28th Annual Int. Conf. IEEE Engineering in Medicine and Biology  Society (EMBC), New York, NY, 2006, pp. 3154--3157.
    359. C. Ebenbauer and F. Allgöwer, “Polynomial Control Systems: Analysis and Design via Dissipation Inequalities,” in Proc. of the 7th Chemical Process Control Conference (CPC), Lake  Lousie, Canada, 2006.
    360. T. Schweickhardt, P. Schumm, U. Münz, and F. Allgöwer, “Integration of E-Learning Modules in Automatic Control Education,” in Proc. 7th IFAC Symp. Advances in Control Education, Madrid, Spain, 2006.
    361. T. Schweickhardt and F. Allgöwer, “Good or bad -- when is plant nonlinearity an obstacle for control?,” in Proc. IFAC Int. Symp. Advanced Control of Chemical Processes (ADCHEM), Gramado, Brazil, 2006, pp. 37–44.
    362. T. Raff, F. Lachner, and F. Allgöwer, “A Finite Time Unknown Input Observer for Linear Systems,” in Proc. 11th Mediterranean Conf. Control and Automation (MED), Ancona, Italy, 2006.
    363. T. Schweickhardt and F. Allgöwer, “An approach to linear control of nonlinear processes,” in Proc. 16th European Symp. Computer Aided Process Engineering (ESCAPE),  9th Int. Symp. Process Systems Engineering (PSE), Garmisch-Partenkirchen, Germany, 2006, pp. 1299–1304.
    364. J. Aßfalg, F. Allgöwer, and M. Fritz, “Constrained derivative-free augmented state estimation for a diesel  engine air path,” in Proc. 14th IFAC Symp. System Identification (SYSID), Newcastle, Australia, 2006, pp. 1382–1387.
    365. M. Journée, T. Schweickhardt, and F. Allgöwer, “Comparative assessment of old and new suboptimal control schemes  on three example processes,” in Proc. 13th IFAC Workshop on Control Applications of Optimization, Paris-Cachan, France, 2006, pp. 189–194.
    366. T. Eißing et al., “Mathematical modeling of TNF induced apoptotic and anti-apoptotic  crosstalk in mammalian cells,” in Conference on Systems Biology of Mammalian Cells (SBMC), 2006, p. 66.
    367. C. Ebenbauer and F. Allgöwer, “Stability analysis for time-delay systems using Rekasius’s substitution  and sum of squares,” in Proc. 45th IEEE Conf. Decision and Control (CDC), San Diego, CA, USA, 2006, pp. 5376--5381.
    368. T. Eißing et al., “Sensitivity analysis of programmed cell death and implications for  crosstalk phenomena during Tumor Necrosis Factor stimulation,” in Proc. IEEE Int. Conf. Control Applications (CCA), Munich, Germany, 2006, pp. 1746–1752.
    369. T. Eißing, F. Allgöwer, P. Scheurich, and E. Bullinger, “Bistability in cell signalling and applications to apoptosis -  principles and robustness aspects,” in Proceedings of the Hamilton Institute International Workshop on  Systems Biology, NUI Maynooth, Ireland, 2006, p. 39.
    370. J. M. Rieber and F. Allgöwer, “Gain-scheduling in the $\ell_1$ framework: a flight control example,” in Proc. 5th IFAC Symp. Robust Control Design, Toulouse, France, 2006.
    371. D. Mayne, S. V. Raković, R. Findeisen, and F. Allgöwer, “Robust output feedback model predictive control for constrained linear  systems under uncertainty based on feed forward and positive invariant  feedback control,” in Proc. 45th IEEE Conf. Decision and Control (CDC), San Diego, CA, USA, 2006, pp. 6618–6623.
    372. T. Eißing, S. Waldherr, F. Allgöwer, and E. Bullinger, “Modelling and Analysis of Death and Survival Signalling:  Achievements and Trends,” in Workshop CNRS-NSF - Biology and control theory: current challenges, Toulouse, France, 2006.
    373. J. Aßfalg and F. Allgöwer, “Fault diagnosis of constrained nonlinear systems using structured augmented state models,” in Proc. IFAC SAFEPROCESS, Beijing, China, 2006, pp. 1375–1380.
    374. M. Farina, R. Findeisen, E. Bullinger, S. Bittanti, F. Allgöwer, and P. Wellstead, “Results towards Identifiability Properties of Biochemical Reaction Networks,” in Proc.\ 45th IEEE Conf.\ Decision and Control (CDC), San Diego, CA, USA, 2006, pp. 2104–2109.
    375. S. Maldonado, S. Borchers, R. Findeisen, and F. Allgöwer, “Modeling bone adaptation and remodeling initiated by mechanical stimuli,” in Proc.\ Int.\ Mediterranean Modelling Conf.\, 2nd European Modeling and Simulation Symp.\ (EMSS), Barcelona, Spain, 2006, pp. 403--409.
    376. R. Lepore, A. Vande Wouwer, M. Remy, R. Findeisen, Z. K. Nagy, and F. Allgöwer, “Scheduled optimization of an MMA polymerization process,” in Proc.\ IFAC Int.\ Symp.\ Advanced Control of Chemical Processes (ADCHEM), Gramado, Brazil, 2006, pp. 695--703.
    377. M. Herceg, T. Raff, R. Findeisen, and F. Allgöwer, “Nonlinear Model Predictive Control of a Turbocharged Diesel Engine,” in Proc.\ IEEE Int.\ Conf.\ Control Applications (CCA), Munich, Germany, 2006, pp. 2766–2771.
    378. S. Maldonado, S. Borchers, R. Findeisen, and F. Allgöwer, “Mathematical Modeling and Analysis of Force Induced Bone Growth,” in Proc.\ 28th Annual Int.\ Conf.\  IEEE Engineering in Medicine and Biology Society (EMBC), New York, NY, 2006, pp. 3154--3157.
    379. C. Ebenbauer and F. Allgöwer, “Polynomial Control Systems:  Analysis and Design via Dissipation Inequalities,” in Proc. of the 7th Chemical Process Control Conference (CPC), Lake Lousie, Canada, 2006.
    380. T. Raff, F. Lachner, and F. Allgöwer, “A Finite Time Unknown Input Observer for Linear Systems,” in Proc.\ 11th Mediterranean Conf.\ Control and Automation (MED), Ancona, Italy, 2006.
    381. T. Eißing, F. Allgöwer, P. Scheurich, and E. Bullinger, “Bistability in cell signalling and applications to apoptosis - principles and robustness aspects,” in Proceedings of the Hamilton Institute International Workshop on Systems Biology, NUI Maynooth, Ireland, 2006, p. 39.
    382. J. M. Rieber and F. Allgöwer, “Gain-scheduling in the $\ell_1$ framework: a flight control example,” in Proc.\ 5th IFAC Symp.\ Robust Control Design, Toulouse, France, 2006.
    383. D. Mayne, S. V. Raković, R. Findeisen, and F. Allgöwer, “Robust output feedback model predictive control for constrained linear systems under uncertainty based on feed forward and positive invariant feedback control,” in Proc.\ 45th IEEE Conf.\ Decision and Control (CDC), San Diego, CA, USA, 2006, pp. 6618–6623.
    384. A. Rehm and F. Allgöwer, “$H_ınfty$ Control of Descriptor Systems in a Differential Inclusion  Setting,” in Proc. American Control Conf. (ACC), Portland, OR, USA, 2005, pp. 4303–4308.
    385. R. Findeisen and F. Allgöwer, “Robustness Properties and Output Feedback of Optimization Based Sampled-data  Open-loop feedback,” in Proc. 44th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Seville, Spain, 2005, pp. 54–59.
    386. Z. K. Nagy, B. Mahn, F. Ruediger, and F. Allgöwer, “Nonlinear model predictive control of batch processes: an industrial  case study,” in Proc. 16th IFAC World Congress, Prague, Czech Republic, 2005.
    387. T. Schweickhardt and F. Allgöwer, “Linear modeling error and steady-state behaviour of nonlinear dynamical  systems,” in Proc. 44th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Seville, Spain, 2005, pp. 8150–8155.
    388. P. Wolfrum, A. Vargas, M. Gallivan, and F. Allgöwer, “Complexity reduction of a thin film deposition model using a trajectory  based nonlinear model reduction technique,” in Proc. American Control Conf. (ACC), Portland, OR, USA, 2005, pp. 2566–2571.
    389. T. Eißing, C. Cimatoribus, F. Allgöwer, P. Scheurich, and E. Bullinger, “System Properties of the Core Reactions of Apoptosis,” in 1st FEBS Advanced Lecture Course Systems Biology, Gosau, Austria, 2005, p. 164.
    390. R. Bars et al., “Theory, algorithms and technology in the design of control systems,” in Proc. 16th IFAC World Congress, Prague, Czech Republic, 2005, pp. 122–131.
    391. T. Sauter et al., “Mathematical modeling of TNF induced apoptotic and anti-apoptotic  crosstalk in mammalian cells,” in 6th International Conference on Systems Biology, Boston, MA, 2005.
    392. C. Ebenbauer, T. Raff, and F. Allgöwer, “A duality-based LPV Approach to Polynomial State Feedback Design,” in Proc. American Control Conf. (ACC), Portland, OR, USA, 2005, pp. 703–708.
    393. R. Roman, Z. K. Nagy, F. Allgöwer, and S. P. Agachi, “Dynamic Modeling and Nonlinear Model Predictive Control of a Fluid  Catalytic Cracking Unit,” in Proc. 15th European Symp. Computer Aided Process Engineering (ESCAPE), Barcelona, Spain, 2005, pp. 1363–1368.
    394. C. Cimatoribus, T. Eißing, N. Elvassore, F. Allgöwer, and E. Bullinger, “Model discrimination tools in apoptosis,” in Proc. 3rd Foundations of Systems Biology in Engineering (FOSBE), Santa Barbara, CA, USA, 2005, pp. 197–200.
    395. J. M. Rieber, A. Fritsch, and F. Allgöwer, “State-space formulas for gain-scheduled $\ell_1$-optimal controllers,” in Proc. American Control Conf. (ACC), Portland, OR, USA, 2005, pp. 609--614.
    396. I. Alvarado, R. Findeisen, P. Kühl, D. Limón, and F. Allgöwer, “State Estimation for Repetitive Processes Using Iteratively Improving  Moving Horizon Observers,” in Proc. 44th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Seville, Spain, 2005, pp. 7756–7761.
    397. T. Raff, P. H. Menold, C. Ebenbauer, and F. Allgöwer, “A Finite Time Functional Observer for Linear Systems,” in Proc. 44th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Seville, Spain, 2005, pp. 7198–7203.
    398. Z. K. Nagy, R. Roman, S. P. Agachi, and F. Allgöwer, “A real-time approach for moving horizon estimation based nonlinear  model predictive control of a fluid catalytic cracking unit,” in Proc. 7th World Congress of Chemical Engineering, Glasgow, Scotland, 2005, pp. 504–510.
    399. C. Hüttner, J. M. Rieber, F. Allgöwer, and J. Hugel, “Compensation of time-varying harmonic disturbances on nonlinear  bearingless slice motors,” in Proc. 16th IFAC World Congress, Prague, Czech Republic, 2005.
    400. C. Ebenbauer, J. Renz, and F. Allgöwer, “Polynomial Feedback and Observer Design using Nonquadratic Lyapunov  Functions,” in Proc. 44th IEEE Conf. Decision and Control (CDC), European Control  Conf. (ECC), Seville, Spain, 2005, pp. 7587–7592.
    401. J. M. Rieber, G. Schitter, A. Stemmer, and F. Allgöwer, “Experimental application of $\ell_1$-optimal control in atomic  force microscopy,” in Proc. 16th IFAC World Congress, Prague, Czech Republic, 2005.
    402. T. Raff, C. Ebenbauer, and F. Allgöwer, “Nonlinear Model Predictive Control: A Passivity-based Approach,” in International Workshop on Assessment and Future Directions of Nonlinear  Model Predictive Control, 2005.
    403. C. Ebenbauer, T. Raff, and F. Allgöwer, “A Simple Separation Result for Control Affine Systems,” in Proc. 16th IFAC World Congres, 2005.
    404. I. R. Ofiteru, V. Lavric, F. Allgöwer, and E. Bullinger, “Sensitivity Analysis of Escherichia coli’s Tricarboxilic  Acid Cycle under Anaerobic Conditions,” in Proc. 3rd Foundations of Systems Biology in Engineering (FOSBE), Santa Barbara, CA, USA, 2005, pp. 337--340.
    405. R. Roman, Z. K. Nagy, F. Allgöwer, S. P. Agachi, and M. Cristea, “Complex dynamic modeling and linear model predictive control of a  fluid catalytic cracking process,” in Proc. 14th Romanian Int. Conf. Chemistry and Chemical Engineering  (RICCE), Bucharest, Romania, 2005, pp. 116–123.
    406. A. Rehm and F. Allgöwer, “$H_ınfty$ Control of Descriptor Systems in a Differential Inclusion Setting,” in Proc.\ American Control Conf.\ (ACC), Portland, OR, USA, 2005, pp. 4303–4308.
    407. R. Findeisen and F. Allgöwer, “Robustness Properties and Output Feedback of Optimization Based Sampled-data Open-loop feedback,” in Proc.\ 44th IEEE Conf.\ Decision and Control (CDC), European Control Conf.\ (ECC), Seville, Spain, 2005, pp. 54–59.
    408. R. Bars et al., “Theory, algorithms and technology in the design of control systems,” in Proc.\ 16th IFAC World Congress, Prague, Czech Republic, 2005, pp. 122–131.
    409. T. Sauter et al., “Mathematical modeling of TNF induced apoptotic and anti-apoptotic crosstalk in mammalian cells,” in 6th International Conference on Systems Biology, Boston, MA, 2005.
    410. C. Ebenbauer, T. Raff, and F. Allgöwer, “A duality-based LPV Approach  to Polynomial State Feedback Design,” in Proc.\ American Control Conf.\ (ACC), Portland, OR, USA, 2005, pp. 703–708.
    411. T. Raff, P. H. Menold, C. Ebenbauer, and F. Allgöwer, “A Finite Time Functional Observer for Linear Systems,” in Proc.\ 44th IEEE Conf.\ Decision and Control (CDC), European Control Conf.\ (ECC), Seville, Spain, 2005, pp. 7198–7203.
    412. C. Hüttner, J. M. Rieber, F. Allgöwer, and J. Hugel, “Compensation of time-varying harmonic disturbances on nonlinear bearingless slice motors,” in Proc.\ 16th IFAC World Congress, Prague, Czech Republic, 2005.
    413. J. M. Rieber, G. Schitter, A. Stemmer, and F. Allgöwer, “Experimental application of $\ell_1$-optimal control in atomic force microscopy,” in Proc.\ 16th IFAC World Congress, Prague, Czech Republic, 2005.
    414. T. Raff, C. Ebenbauer, and F. Allgöwer, “Nonlinear Model Predictive Control: A Passivity-based Approach,” in International Workshop on Assessment and Future Directions of Nonlinear Model Predictive Control, 2005.
    415. C. Ebenbauer, T. Raff, and F. Allgöwer, “A Simple Separation Result for Control Affine Systems,” in Proc.\ 16th IFAC World Congres, 2005.
    416. T. Eißing, H. Conzelmann, E. D. Gilles, F. Allgöwer, E. Bullinger, and P. Scheurich, “Mathematical modeling applied to caspase activation reveals a requirement  for additional control,” in 5th International Conference on Systems Biology, Heidelberg, Germany, 2004, p. 207.
    417. Y. Shastri, T. Schweickhardt, and F. Allgöwer, “Plant and Control-relevant Nonlinearity Analysis of a CSTR: a Case  Study,” in Proc. 7th IFAC Symp. Dynamics and Control of Process Systems (DYCOPS), Cambridge, MA, USA, 2004, pp. 89–94.
    418. A. Rehm and F. Allgöwer, “$H_ınfty$ control of descriptor systems: An application from  binary distillation control,” in Proc. IFAC Int. Symp. Advanced Control of Chemical Processes (ADCHEM), Hong Kong, China, 2004, pp. 351–356.
    419. R. Findeisen and F. Allgöwer, “Stabilization Using Sampled-data Open-Loop Feedback -- a Nonlinear  Model Predictive Control Perspective,” in Proc. 6th IFAC Symp. Nonlinear Control Systems (NOLCOS), Stuttgart, Germany, 2004, pp. 735–740.
    420. T. Raff, C. Ebenbauer, and F. Allgöwer, “Feedback Passivation of an Electrostatic Microactuator: A Semidefinite  Programming Approach,” in Proc. 6th IFAC Symp. Nonlinear Control Systems (NOLCOS), Stuttgart, Germany, 2004, pp. 1181–1186.
    421. Z. K. Nagy, F. Allgöwer, F. Ruediger, and B. Mahn, “Efficient tool for nonlinear model predictive control of batch processes,” in Proc. 12th Mediterranean Conf. Control and Automation (MED), Kusadasi, Turkey, 2004, pp. 1128–1134.
    422. R. Findeisen and F. Allgöwer, “Min-max output feedback predictive control with guaranteed stability,” in Proc. Int. Symp. Mathematical Theory of Networks and Systems (MTNS), Katholieke Universiteit Leuven, Belgium, 2004.
    423. A. Yonchev, R. Findeisen, C. Ebenbauer, and F. Allgöwer, “Model Predictive Control of Linear Continuous Time Singular Systems  Subject to Input Constraints,” in Proc. 43rd IEEE Conf. Decision and Control (CDC), Atlantis, Paradise Island, Bahamas, 2004, pp. 2047–2052.
    424. R. Findeisen and F. Allgöwer, “Computational Delay in Nonlinear Model Predictive Control,” in Proc. IFAC Int. Symp. Advanced Control of Chemical Processes (ADCHEM), Hong Kong, China, 2004, pp. 427–432.
    425. A. Vargas and F. Allgöwer, “Model reduction for process control using iterative nonlinear identification,” in Proc. American Control Conf. (ACC), Boston, MA, USA, 2004, pp. 2915–2920.
    426. A. Rehm and F. Allgöwer, “Causal  $ H_ınfty$ Control of Discrete-time Descriptor Systems:  An LMI Approach in two Steps,” in Proc. 16th Int. Symp. Mathematical Theory of Networks and Systems  (MTNS), Leuven, Belgium, 2004.
    427. C. Ebenbauer and F. Allgöwer, “Computer-aided stability analysis of differential-algebraic equations,” in Proc. 6th IFAC Symp. Nonlinear Control Systems (NOLCOS), Stuttgart, Germany, 2004, pp. 1025--1029.
    428. C. Ebenbauer, R. Findeisen, and F. Allgöwer, “Nonlinear High-Gain Observer Design via Semidefinite Programming,” in Proc. 2nd IFAC Symp. Systems, Structure, and Control (SSSC), Oaxaca, Mexico, 2004, pp. 751–756.
    429. T. Raff, C. Ebenbauer, and F. Allgöwer, “Passivity-based Nonlinear Dynamic Output Feedback Design: A Semidefinite  Programming Approach,” in Proc. 43rd IEEE Conf. Decision and Control (CDC), Atlantis, Paradise Island, Bahamas, 2004, pp. 5409–5414.
    430. C. Ebenbauer and F. Allgöwer, “Minimum-Phase Property of Nonlinear Systems in Terms of a Dissipation  Inequality,” in Proc. American Control Conf. (ACC), Boston, MA, USA, 2004, pp. 1737--1742.
    431. R. Lepore, R. Findeisen, A. Vande Wouwer, F. Allgöwer, and M. Remy, “On open- and closed-loop control of an MMA polymerization reactor,” in Proc. 23rd Benelux Meeting on Systems and Control, Helvoirt, The Netherlands, 2004.
    432. T. Eißing, H. Conzelmann, E. D. Gilles, F. Allgöwer, E. Bullinger, and P. Scheurich, “Mathematical modeling and system analysis of caspase activation,” in International Workshop on Theoretical Biophysics, Hiddensee Island, Germany, 2004, p. 11.
    433. R. Lepore, R. Findeisen, Z. K. Nagy, F. Allgöwer, and A. Vande Wouwer, “Optimal Open- and Closed-Loop Control for Disturbance Rejection in  Batch Process Control: a MMA Polymerization Example,” in Proc. Symp. Knowledge Driven Batch Processes (BatchPro), Poros, Greece, 2004, pp. 235–241.
    434. Z. Nagy, R. Findeisen, and F. Allgöwer, “Hierarchical nonlinear model predictive control of an industrial  batch reactor,” in Proc. Symp. Knowledge Driven Batch Processes (BatchPro), Poros, Greece, 2004, pp. 203–210.
    435. T. Raff, R. Findeisen, C. Ebenbauer, and F. Allgöwer, “Model Predictive Control of Discrete Time Polynomial Control Systems:  A Convex Approach,” in Proc. 2nd IFAC Symp. Systems, Structure, and Control (SSSC), Oaxaca, Mexico, 2004, pp. 158–163.
    436. T. Eißing et al., “Mathematical modeling applied to caspase activation downstream of  death receptors: A missing guardian for caspase 8,” in 2nd International Symposium of the SFB 495, Hohenheim, Germany, 2004.
    437. Z. K. Nagy and F. Allgöwer, “Nonlinear model predictive control: from chemical industries to microelectronics,” in Proc. 43rd IEEE Conf. Decision and Control (CDC), Atlantis, Paradise Island, Bahamas, 2004, pp. 4249–4254.
    438. Y. Shastri, T. Schweickhardt, and F. Allgöwer, “Plant and Control-relevant Nonlinearity Analysis of a CSTR: a Case Study,” in Proc.\ 7th IFAC Symp.\ Dynamics and Control of Process Systems (DYCOPS), Cambridge, MA, USA, 2004, pp. 89–94.
    439. A. Rehm and F. Allgöwer, “$H_ınfty$ control of descriptor systems: An application from binary distillation control,” in Proc.\ IFAC Int.\ Symp.\ Advanced Control of Chemical Processes (ADCHEM), Hong Kong, China, 2004, pp. 351–356.
    440. T. Raff, C. Ebenbauer, and F. Allgöwer, “Feedback Passivation of an Electrostatic Microactuator: A Semidefinite Programming Approach,” in Proc.\ 6th IFAC Symp.\ Nonlinear Control Systems (NOLCOS), Stuttgart, Germany, 2004, pp. 1181–1186.
    441. R. Findeisen and F. Allgöwer, “Min-max output feedback predictive control with guaranteed stability,” in Proc.\ Int.\ Symp.\ Mathematical Theory of Networks and Systems (MTNS), Katholieke Universiteit Leuven, Belgium, 2004.
    442. C. Ebenbauer and F. Allgöwer, “Computer-aided stability analysis of differential-algebraic equations,” in Proc.\ 6th IFAC Symp.\ Nonlinear Control Systems (NOLCOS), Stuttgart, Germany, 2004, pp. 1025--1029.
    443. C. Ebenbauer, R. Findeisen, and F. Allgöwer, “Nonlinear High-Gain Observer Design via Semidefinite Programming,” in Proc.\ 2nd IFAC Symp.\ Systems, Structure, and Control (SSSC), Oaxaca, Mexico, 2004, pp. 751–756.
    444. T. Eißing, H. Conzelmann, E. D. Gilles, F. Allgöwer, E. Bullinger, and P. Scheurich, “Mathematical modeling and system analysis of caspase activation,” in International Workshop on Theoretical Biophysics, Hiddensee Island, Germany, 2004, p. 11.
    445. R. Lepore, R. Findeisen, Z. K. Nagy, F. Allgöwer, and A. Vande Wouwer, “Optimal Open- and Closed-Loop Control for Disturbance Rejection in Batch Process Control: a MMA Polymerization Example,” in Proc.\ Symp.\ Knowledge Driven Batch Processes (BatchPro), Poros, Greece, 2004, pp. 235–241.
    446. Z. Nagy, R. Findeisen, and F. Allgöwer, “Hierarchical nonlinear model predictive control of an industrial batch reactor,” in Proc.\ Symp.\ Knowledge Driven Batch Processes (BatchPro), Poros, Greece, 2004, pp. 203–210.
    447. T. Eißing et al., “Mathematical modeling applied to caspase activation downstream of death receptors: A missing guardian for caspase 8,” in 2nd International Symposium of the SFB 495, Hohenheim, Germany, 2004.
    448. P. H. Menold, R. Findeisen, and F. Allgöwer, “Finite time convergent observers for linear time-varying systems,” in Proc. 11th Mediterranean Conf. Control and Automation (MED), Rhodes, Greece, 2003.
    449. T. Schweickhardt and F. Allgöwer, “How Nonlinear is Nonlinear? An Approach to Nonlinearity Quantification,” in Proceedings of the 7th Philips Conference on Applications of Control  Technology (PACT’03), 2003, pp. 1–14.
    450. T. Schweickhardt, F. Allgöwer, and F. J. Doyle III, “Nonlinearity quantification for the optimal state feedback controller,” in Proc. European Control Conf. (ECC), Cambridge, U.K., 2003, pp. 4611–4617.
    451. N. Hernjak, F. J. Doyle III, F. Allgöwer, and T. Schweickhardt, “Relationship between control-relevant nonlinearity and performance  objective,” in IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM), Hong Kong, China, 2003, pp. 543–548.
    452. M. Diehl, R. Findeisen, F. Allgöwer, J. P. Schlöder, and H. G. Bock, “Stability of Nonlinear Model Predictive Control in the Presence of  Errors due to Numerical Online Optimization,” in Proc. 42nd IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2003, pp. 1419–1424.
    453. P. H. Menold, R. Findeisen, and F. Allgöwer, “Finite time convergent observers for nonlinear systems,” in Proc. 42nd IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2003, pp. 5673--5678.
    454. L. Imsland, R. Findeisen, F. Allgöwer, and B. A. Foss, “Output Feedback Stabilization with Nonlinear Predictive Control -  Asymptotic properties,” in Proc. American Control Conf. (ACC), Denver, CO, USA, 2003, pp. 4908–4913.
    455. A. Rehm and F. Allgöwer, “$H_ınfty$ control of descriptor systems: An application from  binary distillation control,” in Proc. European Control Conf. (ECC), Cambridge, UK, 2003.
    456. P. H. Menold and F. Allgöwer, “Finite time convergent observer,” in AIChE Annual Meeting, San Francisco, CA, USA, 2003.
    457. G. Schitter, A. Stemmer, and F. Allgöwer, “Robust 2DOF-control of a piezoelectric tube scanner for high speed  atomic force microscopy,” in Proc. American Control Conf. (ACC), Denver, CO, USA, 2003, pp. 3720–3725.
    458. P. Schumm, T. Schweickhardt, E. Bullinger, and F. Allgöwer, “Der Einsatz neuer Medien in der regelungstechnischen Ausbildung,” in Proc. GMA-Kongress, Baden-Baden, Germany, 2003, pp. 1061–1068.
    459. T. Schweickhardt, F. Allgöwer, and F. J. Doyle III, “The optimal control law nonlinearity measure: Improving control-relevant  nonlinearity assessment,” in AIChE Annual Meeting, San Francisco, CA, USA, 2003.
    460. J. M. Rieber and F. Allgöwer, “An approach to gain-scheduled $\ell_1$-optimal control of linear  parameter-varying systems,” in Proc. 42nd IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2003, pp. 6109--6114.
    461. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Stability Conditions for Observer Based Output Feedback Stabilization  with Nonlinear Model Predictive Control,” in Proc. 42nd IEEE Conf. Decision and Control (CDC), Maui, HI, USA, 2003, pp. 1425--1430.
    462. R. Findeisen and F. Allgöwer, “Theorie und Anwendung der nichtlinearen prädiktiven Regelung,” in Proc. of GMA-Gesellschaft für Meß- und Automatisierungstechnik  annual meeting, Baden-Baden, Germany, 2003.
    463. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Output-feedback Nonlinear Model Predictive Control using High-Gain  Observers in Original Coordinates,” in Proc. European Control Conf. (ECC), Cambridge, UK, 2003, pp. 2061–2066.
    464. N. Hernjak, F. J. Doyle III, F. Allgöwer, and T. Schweickhardt, “Relationship between control-relevant nonlinearity and performance objective,” in IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM), Hong Kong, China, 2003, pp. 543–548.
    465. P. H. Menold, R. Findeisen, and F. Allgöwer, “Finite time convergent observers for nonlinear systems,” in Proc.\ 42nd IEEE Conf.\ Decision and Control (CDC), Maui, HI, USA, 2003, pp. 5673--5678.
    466. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Output-feedback Nonlinear Model Predictive Control using High-Gain Observers in Original Coordinates,” in Proc.\ European Control Conf.\ (ECC), Cambridge, UK, 2003, pp. 2061–2066.
    467. C. W. Scherer, H. Chen, and F. Allgöwer, “Disturbance Attenuation with Actuator Constraints by Hybrid State  Feedback Control,” in Proc. 41st IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2002, pp. 4134–4139.
    468. L. Magni, G. de Nicolao, R. Scattolini, and F. Allgöwer, “Robust receding horizon control for nonlinear discrete-time systems,” in Proc. 15th IFAC World Congress, Barcelona, Spain, 2002.
    469. A. Rehm and F. Allgöwer, “An LMI Approach towards $H_ınfty$ Control of Discrete-time  Descriptor Systems,” in Proc. American Control Conf. (ACC), Minneapolis, MN, USA, 2002, pp. 614–619.
    470. R. Findeisen et al., “Computation and Performance Assesment of Nonlinear Model Predictive  Control,” in Proc. 41st IEEE Conf. Decision and Control (CDC), Las Vegas, NV, USA, 2002, pp. 4613–4618.
    471. R. Findeisen, M. Diehl, T. Bürner, F. Allgöwer, H. G. Bock, and J. P. Schlöder, “Efficient Output Feedback Nonlinear Model Predictive Control,” in Proc. American Control Conf. (ACC), Anchorage, AK, USA, 2002, pp. 4752–4757.
    472. Z. Nagy et al., “The tradeoff between modelling complexity and real-time feasibility  in nonlinear model predictive control.,” in Proc. 6th World Multiconference on Systemics, Cybernetics and Informatics  (SCI), Orlando, FL, USA, 2002, pp. 329–334.
    473. A. Rehm and F. Allgöwer, “An LMI Approach towards Stabilization of Discrete-time Descriptor  Systems,” in Proc. 15th IFAC World Congress, Barcelona, Spain, 2002.
    474. H. W. Knobloch, C. Ebenbauer, and F. Allgöwer, “A framework for disturbance attenuation with discontinuous control,” in Proc. 15th IFAC World Congres, Barcelona, Spain, 2002.
    475. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Output feedback nonlinear predictive control - A separation principle  approach.,” in Proc. 15th IFAC World Congress, Barcelona, Spain, 2002.
    476. F. Allgöwer, Z. Nagy, and R. Findeisen, “Nonlinear Model Predictive Control: From Theory to Application,” in Proc. Int. Symp. Design, Operation and Control of Chemical Plants  (PSE), Taipei, Taiwan, 2002, pp. 639–650.
    477. E. Bullinger, T. Sauter, F. Allgöwer, and E. D. Gilles, “On deriving a hybrid model for Carbohydrate Uptake in Escherichia  col,” in Proc. 15th IFAC World Congress, Barcelona, Spain, 2002.
    478. A. Rehm and F. Allgöwer, “An LMI Approach towards $H_ınfty$ Control of Discrete-time Descriptor Systems,” in Proc.\ American Control Conf.\ (ACC), Minneapolis, MN, USA, 2002, pp. 614–619.
    479. R. Findeisen, M. Diehl, T. Bürner, F. Allgöwer, H. G. Bock, and J. P. Schlöder, “Efficient Output Feedback Nonlinear Model Predictive Control,” in Proc.\ American Control Conf.\ (ACC), Anchorage, AK, USA, 2002, pp. 4752–4757.
    480. Z. Nagy et al., “The tradeoff between modelling complexity and real-time feasibility in nonlinear model predictive control.,” in Proc.\ 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI), Orlando, FL, USA, 2002, pp. 329–334.
    481. M. Niethammer, P. H. Menold, and F. Allgöwer, “Parameter and Derivative Estimation for Nonlinear Continuous-Time  System Identification,” in Proc. 5th IFAC Symp. Nonlinear Control Systems (NOLCOS), St. Petersburg, Russia, 2001, pp. 691–696.
    482. R. Findeisen, Z. Nagy, M. Diehl, F. Allgöwer, H. G. Bock, and J. P. Schlöder, “Computational feasibility and performance of nonlinear model predicitve  control.,” in Proc. European Control Conf. (ECC), Porto, Portugal, 2001, pp. 957--961.
    483. Z. Nagy et al., “Using Genetic Algorithm in Robust Nonlinear Model Predictive Control,” in Proc. 11th European Symp. Computer Aided Process Engineering (ESCAPE), Kolding, Denmark, 2001, pp. 711–716.
    484. L. Imsland, R. Findeisen, E. Bullinger, F. Allgöwer, and B. A. Foss, “On Output feedback Nonlinear Model Predictive Control using high  gain observers for a class of systems,” in Proc. 6th IFAC Symp. Dynamics and Control of Process Systems (DYCOPS), Jejudo, Korea, 2001, pp. 91–96.
    485. Z. Nagy, S. P. Agachi, F. Allgöwer, and R. Findeisen, “Nonlinear model predictive control of a high purity distillation  column,” in 14-th International Congress of Chemical and Process Engineering  CHISA 2000, Prague, Czech Republic, 2001.
    486. A. Kremling, T. Sauter, E. Bullinger, M. Ederer, F. Allgöwer, and E. D. Gilles, “Biosystems Engineering: Applying methods from systems theory to biological  systems,” in Proc. 2nd Int. Conf. Systems Biology, Pasadena, CA, USA, 2001, pp. 282--290.
    487. R. K. Pearson, P. H. Menold, and F. Allgöwer, “Structured Outliers and Data Cleaning Filters,” in Proceedings of the IEEE-EURASIP Nonlinear Signal and Image Processing  workshop, NSIP-01, Baltimore, MD, USA, 2001.
    488. E. Bullinger, R. Findeisen, and F. Allgöwer, “Adaptive $łambda$-Tracking of Nonlinear Systems with Higher Relative  Degree Using Reduced-Order High Gain Control,” in Proc. 5th IFAC Symp. Nonlinear Control Systems (NOLCOS), St. Petersburg, Russia, 2001, pp. 92–97.
    489. H. Chen and F. Allgöwer, “Nonlinear model predictive control of a class of mechatronic systems,” in Proc. 4th China-Korea Joint Workshop on Process Systems Engineering, Guangzhou, China, 2001, pp. 65–72.
    490. L. Imsland, R. Findeisen, E. Bullinger, F. Allgöwer, and B. A. Foss, “On Output feedback Nonlinear Model Predictive Control using high gain observers for a class of systems,” in Proc.\ 6th IFAC Symp.\ Dynamics and Control of Process Systems (DYCOPS), Jejudo, Korea, 2001, pp. 91–96.
    491. R. K. Pearson, P. H. Menold, and F. Allgöwer, “Structured Outliers and Data Cleaning Filters,” in Proceedings of the IEEE-EURASIP Nonlinear Signal and Image Processing workshop, NSIP-01, Baltimore, MD, USA, 2001.
    492. E. Bullinger, R. Findeisen, and F. Allgöwer, “Adaptive $łambda$-Tracking of Nonlinear Systems with Higher Relative Degree Using Reduced-Order High Gain Control,” in Proc.\ 5th IFAC Symp.\ Nonlinear Control Systems (NOLCOS), St. Petersburg, Russia, 2001, pp. 92–97.
    493. E. Bullinger, R. Findeisen, F. J. Kraus, and F. Allgöwer, “Some further Results on Adaptive $łambda$-tracking for Linear Systems  with High Relative Degree,” in Proc. American Control Conf. (ACC), Chicago, IL, USA, 2000, pp. 3655–3659.
    494. R. Findeisen, H. Chen, and F. Allgöwer, “Nonlinear Predictive Control for Setpoint Families,” in Proc. American Control Conf. (ACC), Chicago, IL, USA, 2000, pp. 260–264.
    495. E. Bullinger and F. Allgöwer, “Adaptive $łambda$-tracking for Nonlinear Systems with Higher Relative  Degree,” in Proc. 39th IEEE Conf. Decision and Control (CDC), Sydney, Australia, 2000, pp. 4771–4776.
    496. Z. Nagy et al., “Real-time Feasibility of Nonlinear Predictive Control for Large Scale  Processes -- a Case Study,” in Proc. American Control Conf. (ACC), Chicago, IL, USA, 2000, pp. 4249--4254.
    497. R. Findeisen, F. Allgöwer, M. Diehl, H. G. Bock, J. P. Schlöder, and Z. Nagy, “Efficient Nonlinear Model Predictive Control,” in Proc. 6th Int. Conf. Chemical Process Control (CPC), Tuscon, AZ, USA, 2000, pp. 454–460.
    498. E. Bullinger, C. W. Frei, T. J. Sieber, A. H. Glattfelder, F. Allgöwer, and A. M. Zbinden, “Adaptive $łambda$-tracking in Anesthesia,” in Proc. 4th IFAC Symp. Modelling and Control in Biomedical Systems, Oxford, UK, 2000, pp. 181–186.
    499. F. Allgöwer, R. Findeisen, Z. Nagy, M. Diehl, H. G. Bock, and J. P. Schlöder, “Efficient Nonlinear Model Predictive Control for Large Scale Constrained  Processes,” in Proc. 6th Int. Conf. Methods and Models in Automation and Robotics, 2000, pp. 43–54.
    500. R. Findeisen, F. Allgöwer, M. Diehl, H. G. Bock, J. P. Schlöder, and Z. Nagy, “Efficient Nonlinear Model Predictive Control,” in Proc.\ 6th Int.\ Conf.\ Chemical Process Control (CPC), Tuscon, AZ, USA, 2000, pp. 454–460.
    501. E. Bullinger and F. Allgöwer, “Adaptive $łambda$-tracking for Linear Systems with Higher Relative  Degree --- The Continuous Adaptation Case,” in Proc. European Control Conf. (ECC), Karlsruhe, Germany, 1999.
    502. E. Bullinger, A. Ilchmann, and F. Allgöwer, “Piecewise Constant High-Gain Adaptive $łambda$-tracking for Higher  Relative Degree Linear Systems,” in Proc.\ of the 14th IFAC World Congress, Beijing, China, Beijing, China, 1999, vol. D, pp. 249–254.
    503. P. H. Menold, R. K. Pearson, and F. Allgöwer, “Online outlier detection and removal,” in Proc. 7th Mediterranean Conf. Control and Automation (MED), Haifa, Israel, 1999, pp. 1110–1133.
    504. E. Bullinger and F. Allgöwer, “Adaptive $łambda$-tracking for Linear Systems with Higher Relative Degree --- The Continuous Adaptation Case,” in Proc.\ European Control Conf.\ (ECC), Karlsruhe, Germany, 1999.
    505. E. Bullinger, A. Ilchmann, and F. Allgöwer, “Piecewise Constant High-Gain Adaptive $łambda$-tracking for Higher Relative Degree Linear Systems,” in Proc.\ of the 14th IFAC World Congress, Beijing, China, Beijing, China, 1999, vol. D, pp. 249–254.
    506. P. H. Menold, R. K. Pearson, and F. Allgöwer, “Online outlier detection and removal,” in Proc.\ 7th Mediterranean Conf.\ Control and Automation (MED), Haifa, Israel, 1999, pp. 1110–1133.
    507. H. Chen, C. W. Scherer, and F. Allgöwer, “A robust model predictive control scheme for constrained linear systems,” in Proc. 5th IFAC Symp. Dynamics and Control of Process Systems (DYCOPS), Corfu, Greece, 1998, pp. 60–65.
    508. R. K. Pearson, P. H. Menold, and F. Allgöwer, “Practically-motivated input sequences for nonlinear model identification,” in Proc. American Control Conf. (ACC), Philadelphia, PA, USA, 1998, pp. 1235–1239.
    509. H. Chen, C. W. Scherer, and F. Allgöwer, “A robust model predictive control scheme for constrained linear systems,” in Proc.\ 5th IFAC Symp.\ Dynamics and Control of Process Systems (DYCOPS), Corfu, Greece, 1998, pp. 60–65.
    510. H. Chen and F. Allgöwer, “A quasi-infinite horizon nonlinear predictive control scheme for  stable systems: Application to a CSTR,” in Proc. IFAC Int. Symp. Advanced Control of Chemical Processes (ADCHEM), Banff, Canada, 1997, pp. 471–476.
    511. H. Chen and F. Allgöwer, “Quasi-infinite horizon nonlinear predictive control,” in Workshop on Control of Nonlinear and Uncertain Systems (COSY), London, UK, 1997, pp. 52–57.
    512. H. Chen and F. Allgöwer, “A quasi-infinite horizon nonlinear model predictive control scheme  with guaranteed stability,” in Proc. European Control Conf. (ECC), 1997.
    513. P. H. Menold, F. Allgöwer, and R. K. Pearson, “On simple representation of distillation dynamics,” in Proc. 1st European Congress on Chemical Engineering (ECCE), Florence, Italy, 1997, pp. 1363–1366.
    514. E. Bullinger and F. Allgöwer, “An Adaptive High-Gain Observer for Nonlinear Systems,” in Proc. 36th IEEE Conf. Decision and Control (CDC), San Diego, CA, USA, 1997, pp. 4348--4353.
    515. H. Chen, C. W. Scherer, and F. Allgöwer, “A game theoretic approach to nonlinear robust receding horizon control  of constrained systems,” in Proc. American Control Conf. (ACC), Albuquerque, NM, USA, 1997, pp. 3073–3077.
    516. R. K. Pearson, F. Allgöwer, and P. H. Menold, “Stochastic suitability measures for nonlinear structure identification,” in Proc. European Control Conf. (ECC), Bruessels, Belgium, 1997.
    517. H. Chen and F. Allgöwer, “A quasi-infinite horizon predictive control scheme for constrained  nonlinear systems,” in Proc. 16th Chinese Control Conf., Qindao, China, 1996, pp. 309–316.
    518. H. Chen, A. Kremling, and F. Allgöwer, “Nonlinear predictive control of a benchmark CSTR,” in Proc. European Control Conf. (ECC), Rome, Italy, 1995, pp. 3247–3252.
    519. H. Chen and F. Allgöwer, “Maximal yield control of a nonlinear chemical reactor,” in Proc. 1st IFAC Youth Automation Conf. (YAC), Beijing, China, 1995, pp. 764–769.
    520. H. Chen, A. Kremling, and F. Allgöwer, “Nonlinear predictive control of a benchmark CSTR,” in Proc.\ European Control Conf.\ (ECC), Rome, Italy, 1995, pp. 3247–3252.
  5. misc

    1. J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Data-Driven Model Predictive Control with Stability and Robustness Guarantees.” 2019.
    2. S. Linsenmayer and F. Allgöwer, “Control over Networks Using a Slotted Transmission Classication Model.” 2019.
    3. S. Linsenmayer and F. Allgöwer, “Networked Control Systems with advanced interfaces between control and communication.” 2018.
    4. W. Halter and F. Allgöwer, “Regelungstechnik in der Synthetischen Biologie: Konzeptionelle und experimentelle Realisierung von PID Reglern im Inneren von Zellen.” 2018.
    5. J. Köhler and F. Allgöwer, “Robust reference tracking with Model Predictive Control.” 2018.
    6. J. Berberich, J. Köhler, F. Allgöwer, and M. A. Müller, “Indefinite linear quadratic optimal control: periodic dissipativity and turnpike properties.” 2018.
    7. K. Kuritz and F. Allgöwer, “Broadcast control of oscillating cell populations.” 2018.
    8. K. Kuritz and F. Allgöwer, “Therapy design by broadcast control of oscillating cell populations.” 2018.
    9. J. Berberich and F. Allgöwer, “A convex relaxation for learning linear dynamical systems with nonlinear sensors.” 2018.
    10. S. Linsenmayer and F. Allgöwer, “Event-based sampling concepts for Networked Control Systems.” 2017.
    11. D. Imig, N. Pollak, and F. Allgöwer, “Cell population dynamics during apoptotic treatment.” 2017.
    12. S. Linsenmayer and F. Allgöwer, “On the potential of event-based sampling for control with limited  data rate.” 2017.
    13. S. Linsenmayer and F. Allgöwer, “Stability analysis and control design for weakly hard real-time systems.” 2017.
    14. S. Linsenmayer and F. Allgöwer, “Event-based methods in Net-CPS: An example and arising challenges.” 2016.
    15. K. Kuritz, F. Müller, N. Pollak, and F. Allgöwer, “Too Young to Die: Age Structured Population Models Capture Cell Cycle  Dependent Apoptosis from Snapshot Data.” 2016.
    16. K. Kuritz and F. Allgöwer, “Inferring cell-cycle dependent signalling with age-structured population  models.” 2015.
    17. K. Kuritz and F. Allgöwer, “Inferring cell-cycle dependent signalling with age-structured population models.” 2015.
    18. K. Kuritz and F. Allgöwer, “Determining cell-cycle induced variations from snap-shot data sets.” 2014.
    19. D. Imig et al., “Simulations and predictions of TRAIL response in lung cancer cell  populations via mathematical modeling.” 2014.
    20. D. Imig, T. Strecker, N. Pollak, P. Scheurich, F. Allgöwer, and S. Waldherr, “Simulations and predictions of the response of heterogeneous cancer  cell populations to apoptosis induction.” 2014.
    21. K. Kuritz and F. Allgöwer, “Determining cell-cycle induced variations from snap-shot data sets.” 2014.
    22. D. Imig et al., “Simulations and predictions of TRAIL response in lung cancer cell populations via mathematical modeling.” 2014.
    23. D. Schittler, G. Vacun, H. Walles, J. Hansmann, F. Allgöwer, and S. Waldherr, “Towards a dynamical model of gene regulation in mesenchymal stem  cell differentiation.” 2012.
    24. S. Waldherr, R. Buschow, J. Isensee, F. Allgöwer, and T. Hucho, “Cellular heterogeneity in neuronal pain sensing.” 2012.
    25. D. Schittler, G. Vacun, H. Walles, J. Hansmann, F. Allgöwer, and S. Waldherr, “Towards a dynamical model of gene regulation in mesenchymal stem cell differentiation.” 2012.
    26. D. Schittler, C. Breindl, and F. Allgöwer, “Model selection of networks that are robust against kinetic uncertainties.” 2011.
    27. S. Waldherr and F. Allgöwer, “Robustness analysis of biomolecular networks via polynomial programming.” May-2011.
    28. D. Schittler, G. Vacun, J. Hansmann, F. Allgöwer, and S. Waldherr, “Modeling gene regulatory networks of mesenchymal stem cell differentiation.” 2011.
    29. M. A. Müller, M. Reble, and F. Allgöwer, “Distributed MPC for cooperative control.” 2011.
    30. S. Waldherr and F. Allgöwer, “Reliable ovarian follicle development through a stochastic bistable  switch with cell-cell interactions.” 2011.
    31. J. Hasenauer, S. Waldherr, M. Doszczak, P. Scheurich, N. Radde, and F. Allgöwer, “From single-cell models to mechanicstic population descriptions -  A modeling, simulation, and analysis framework.” 2011.
    32. D. Schittler, S. Waldherr, and F. Allgöwer, “Switch models for cell differentiation: Bifurcation analysis reveals  distinct switching properties.” 2010.
    33. D. Schittler, S. Waldherr, J. Hasenauer, and F. Allgöwer, “Modeling genetic switching in osteoblast cell fate driven by extrinsic  and intrinsic signals.” 2010.
    34. D. Schittler et al., “Model-based design of osteoblast differentiation stimuli.” 2010.
    35. D. Schittler, S. Waldherr, and F. Allgöwer, “Switch models for cell differentiation: Bifurcation analysis reveals distinct switching properties.” 2010.
    36. S. Waldherr and F. Allgöwer, “A feedback approach to bifurcation analysis in biochemical networks  with many parameters.” Oct-2009.
    37. R. Blind, U. Münz, and F. Allgöwer, “Modeling, Analysis, and Stabilization of Networked Control Systems:  A Jump Linear Systems Approach.” 2008.
    38. R. Blind, U. Münz, and F. Allgöwer, “Modeling, Analysis, and Stabilization of Networked Control Systems: A Jump Linear Systems Approach.” 2008.
    39. K. L. Knierim, J. Maess, M. Schneider, and F. Allgöwer, “Regelung eines Achterbahn-Kettenliftes.” 2007.
    40. K. L. Knierim, J. Maess, M. Schneider, and F. Allgöwer, “Regelung eines Achterbahn-Kettenliftes.” 2007.
    41. S. Maldonado, S. Borchers, R. Findeisen, and F. Allgöwer, “Modeling and Analysis of Force Induced Bone Growth.” 2006.
    42. I. Alvarado, R. Findeisen, P. Kühl, D. Limón, and F. Allgöwer, “Iteratively Improving Moving Horizon Observers for Repetitive Processes.” 2006.
    43. S. Borchers, S. Maldonado, R. Findeisen, and F. Allgöwer, “Modeling the bone remodeling cycle due to mechanical force.” 2006.
    44. I. Alvarado, R. Findeisen, P. Kühl, D. Limón, and F. Allgöwer, “Iteratively Improving Moving Horizon Observers for Repetitive Processes.” 2006.
    45. S. Borchers, S. Maldonado, R. Findeisen, and F. Allgöwer, “Modeling the bone remodeling cycle due to mechanical force.” 2006.
    46. T. Eißing, P. Scheurich, and F. Allgöwer, “To Be or Not to Be - Mathematical Systems Theory to  Analyze Biological Signal Processing.” 2005.
    47. R. Findeisen and F. Allgöwer, “Modeling and Analysis of Bone Growth and Remodeling.” 2005.
    48. R. Roman, Z. K. Nagy, S. P. Agachi, and F. Allgöwer, “First principles modeling and nonlinear optimization based estimation  and control of a fluid catalytic cracking unit.” 2005.
    49. R. Findeisen and F. Allgöwer, “Output-Feedback Nonlinear Model Predictive Control for Chemical Processes  without the Need of Fast Observers.” 2005.
    50. R. Findeisen and F. Allgöwer, “Modeling and Analysis of Bone Growth and Remodeling.” 2005.
    51. R. Roman, Z. K. Nagy, S. P. Agachi, and F. Allgöwer, “First principles modeling and nonlinear optimization based estimation and control of a fluid catalytic cracking unit.” 2005.
    52. R. Findeisen and F. Allgöwer, “Output-Feedback Nonlinear Model Predictive Control for Chemical Processes without the Need of Fast Observers.” 2005.
    53. R. Findeisen and F. Allgöwer, “Prädiktive Ausgangsregelung mit Stabilitätsgarantie.” 2004.
    54. R. Findeisen, T. Raff, and F. Allgöwer, “Prädiktive Ausgangsregelung nichtlinearer verfahrenstechnischer  Prozesse: Praktische und theoretische Aspekte.” 2004.
    55. J. M. Rieber, F. Allgöwer, and A. Stemmer, “Schneller sehen durch Regelungstechnik -- Moderne Bildgebung  in der Nanotechnologie.” 2004.
    56. Z. Nagy, R. Findeisen, and F. Allgöwer, “Nonlinear model predictive control approach for robust run-to-run  control of batch processes.” 2004.
    57. Z. K. Nagy, R. Findeisen, and F. Allgöwer, “Nonlinear Model Predictive Control of Batch Processes.” 2004.
    58. R. Findeisen and F. Allgöwer, “Prädiktive Ausgangsregelung mit Stabilitätsgarantie.” 2004.
    59. R. Findeisen, T. Raff, and F. Allgöwer, “Prädiktive Ausgangsregelung nichtlinearer verfahrenstechnischer Prozesse: Praktische und theoretische Aspekte.” 2004.
    60. J. M. Rieber, F. Allgöwer, and A. Stemmer, “Schneller sehen durch Regelungstechnik -- Moderne Bildgebung in der Nanotechnologie.” 2004.
    61. F. Allgöwer, R. Findeisen, and C. Ebenbauer, “Nonlinear Model Predictive Control.” 2003.
    62. F. Allgöwer, R. Findeisen, and C. Ebenbauer, “Nonlinear Model Predictive Control.” 2003.
    63. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Output Feedback Nonlinear Predictive Control.” 2002.
    64. L. Imsland, R. Findeisen, F. Allgöwer, and B. A. Foss, “Output Feedback Nonlinear Model Predictive Control.” 2002.
    65. F. Allgöwer et al., “Tutorial workshop on computational efficiency in linear and non-linear  predictive control.” 2002.
    66. F. Allgöwer and R. Findeisen, “Nonlinear Model Predictive Control of Chemical Processes.” 2001.
    67. R. Findeisen and F. Allgöwer, “An introduction to nonlinear model predictive control.” 2001.
    68. R. Findeisen and F. Allgöwer, “An introduction to nonlinear model predictive control.” 2001.
    69. G. Schitter, P. H. Menold, H. Knapp, A. Stemmer, and F. Allgöwer, “Simulation and open loop identification of tapping mode atomic force  microscopy.” 2000.
    70. G. Schitter, P. H. Menold, H. Knapp, A. Stemmer, and F. Allgöwer, “Intelligent Control for the next generation of fast scanning atomic  force microscopes.” 1999.
    71. E. Bullinger and F. Allgöwer, “Ein adaptiver high-gain Beobachter für nichtlineare Systeme.” 1997.
    72. P. H. Menold and F. Allgöwer, “Struktureignungsmaße zur nichtlinearen Systemidentifikation.” 1997.
    73. E. Bullinger and F. Allgöwer, “Ein adaptiver high-gain Beobachter für nichtlineare Systeme.” 1997.
    74. P. H. Menold and F. Allgöwer, “Struktureignungsmaße zur nichtlinearen Systemidentifikation.” 1997.
  6. techreport

    1. D. Schittler, T. Jouini, F. Allgöwer, and S. Waldherr, “Generalization of the construction method for multistability-equivalent  gene regulatory networks to systems with multi-input multi-output  loopbreaking,” arXiv:1312.7250v2, 2013.
    2. D. Schittler, T. Jouini, F. Allgöwer, and S. Waldherr, “Generalization of the construction method for multistability-equivalent gene regulatory networks to systems with multi-input multi-output loopbreaking,” arXiv:1312.7250v2, 2013.
    3. J. M. Rieber and F. Allgöwer, “Mixed $\ell_1/H_ınfty$ control of MIMO systems:  a linear matrix inequality approach,” Institute for Systems Theory in Engineering, University of Stuttgart, Stuttgart, Germany, Technical report, 2005.
    4. J. M. Rieber and F. Allgöwer, “Mixed $\ell_1/H_ınfty$ control of MIMO systems: a linear matrix inequality approach,” Institute for Systems Theory in Engineering, University of Stuttgart, Stuttgart, Germany, Technical report, 2005.
    5. T. Schweickhardt and F. Allgöwer, “Trajectory-based approximate optimal controller synthesis,” Institute for Systems Theory in Engineering, University of Stuttgart,  Germany, 2004.
  7. unpublished

    1. R. Findeisen and F. Allgöwer, “Nonlinear Model Predictive Control,” 2003.
    2. R. Findeisen and F. Allgöwer, “Nonlinear Model Predictive Control,” 2003.
    3. R. Findeisen, L. Imsland, F. Allgöwer, and B. A. Foss, “Semi-regional stability results for output-feedback nonlinear predictive  control,” 2002.

Frank Allgöwer is professor in the Mechanical Engineering Department of the University of Stuttgart in Germany, director of the Institute for Systems Theory and Automatic Control (IST) and director of the Stuttgart Research Centre for Systems Biology (SRCSB). He studied Engineering Cybernetics and Applied Mathematics in Stuttgart and at the University of California at Los Angeles (UCLA) respectively and received his Ph.D. degree from the University of Stuttgart. Prior to his present appointment he held an assistant professorship in the electrical engineering department at ETH Zurich and visiting positions at Caltech, the NASA Ames Research Center, the DuPont Company, the University of California at Santa Barbara and the University of Newcastle in Australia. Since 2012 Frank serves in addition as Vice-President of Germany’s most important research funding agency, the German Research Foundation (DFG) in Bonn, Germany.

Frank's main interests in research and teaching are in the area of systems and control with emphasis on the development of new methods for the analysis and control of nonlinear systems, networks of systems, optimization based control and data based control. His application interests span a wide range from chemical engineering via mechatronic systems to systems biology. He has published over 500 scientific articles on his research and received several recognitions including several best paper awards, an IFAC Fellowship, the IFAC Outstanding Service Award, the IEEE CSS Distinguished Member Award, the State Teaching Award of the German state of Baden-Württemberg, and the Leibniz Prize, which is the most prestigious award in science and engineering awarded by the Deutsche Forschungsgemeinschaft.

Frank served IFAC in many positions over the last two decades. Among others he was Editor for IFAC’s flagship journal Automatica for 13 years, chairman of the IFAC Technical Committee on Nonlinear Systems, Member of IFAC’s Policy Committee, Member of the IFAC Council and Chair of the Administration and Finance Committee. Since 2017 he is President of IFAC until the Berlin World Congress in 2020.

In addition to his activities within IFAC, Frank is also involved in other scientific and societal organizations. He served, for example, the IEEE Control Systems Society as Vice-president for Technical Activities in 2013/14, was repeatedly a member of IEEE CSS Board of Governors, and has been the chairman of the CSS International Affairs Committee for 2007-2013. In addition he has been a member of the council of the European Union Control Association (EUCA) and a member of the Board of Governors of the VDI/VDE Society for Measurement and Automatic Control. Frank has been organizer or co-organizer of more than a dozen international conferences.

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