This picture showsFrank Allgöwer

Prof. Dr.-Ing.

Frank Allgöwer

Head of institute
Institute for Systems Theory and Automatic Control

Contact

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

Pfaffenwaldring 9
70569 Stuttgart
Germany
Room: 2.246

Office Hours

The office hours of Prof. Allgöwer will be conducted via WebEx at
https://unistuttgart.webex.com/meet/frank.allgoewer
and take place Monday 1 - 2 pm and Friday 12 noon - 1 pm.

  1. (Journal-) Articles

    1. T. Martin and F. Allgöwer, “Data-driven inference on optimal input-output properties of polynomial systems with focus on nonlinearity measures,” IEEE Trans. Automat. Control (submitted), Preprint: arXiv:2103.10306, 2021.
    2. J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Data-driven model predictive control: closed-loop guarantees and experimental results,” at-Automatisierungstechnik, 2021.
    3. J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Linear tracking MPC for nonlinear systems part II: the data-driven case,” IEEE Trans. Automat. Control, 2021.
    4. J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Linear tracking MPC for nonlinear systems part I: the model-based case,” IEEE Trans. Automat. Control, 2021.
    5. S. Linsenmayer, M. Hertneck, and F. Allgöwer, “Linear Weakly Hard Real-Time Control Systems: Time- and Event-Triggered Stabilization,” IEEE Trans.\ Automat.\ Control, vol. 66, no. 4, Art. no. 4, 2021, doi: 10.1109/TAC.2020.3000981.
    6. J. Köhler, R. Soloperto, M. A. Müller, and F. Allgöwer, “A computationally efficient robust model predictive control framework for uncertain nonlinear systems,” IEEE Trans. Automat. Control, 2020.
    7. J. Köhler, M. A. Müller, and F. Allgöwer, “Nonlinear reference tracking: An economic model predictive control perspective,” IEEE Trans. Automat. Control, vol. 64, pp. 254–269, 2018.
    8. M. Hertneck, J. Köhler, S. Trimpe, and F. Allgöwer, “Learning an approximate model predictive controller with guarantees,” IEEE Control Systems Lett., vol. 2, no. 3, Art. no. 3, 2018, doi: 10.1109/LCSYS.2018.2843682.
    9. K. D. Listmann, P. Wenzelburger, and F. Allgöwer, “Industrie 4.0 - (R)evolution ohne Regelungstechnik?,” at-Automatisierungstechnik, vol. 64, no. 7, Art. no. 7, 2016, doi: 10.1515/auto-2016-0039.
    10. 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, Art. no. 11, 2014.
    11. R. Krause et al., “Scientific workflows for bone remodelling simulations,” Proceedings in Applied Mathematics and Mechanics, 2013.
    12. 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.
    13. 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.
    14. 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, Art. no. 5, 2009.
    15. 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, Art. no. 1, 2008.
    16. A. Kremling et al., “A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions,” Genome Research, vol. 14, no. 9, Art. no. 9, 2004.
    17. 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. Contributions to anthologies

    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. 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.
    3. 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.
  3. Conference papers

    1. M. Hertneck, S. Linsenmayer, and F. Allgöwer, “Stability Analysis for Nonlinear Weakly Hard Real-Time Control Systems,” in Proc. 21st IFAC World Congress, Berlin, Germany, 2020, pp. 2632–2637, doi: 10.1016/j.ifacol.2020.12.307.
    2. M. Hertneck and F. Allgöwer, “Exploiting Information for Decentralized Periodic Event-Triggered Control,” in Proc. 59th IEEE Conf. Decision and Control (CDC), Jeju, South Korea, 2020, pp. 4999–5004, doi: 10.1109/CDC42340.2020.9304456.
    3. T. Martin, A. Koch, and F. Allgöwer, “Data-driven surrogate models for LTI systems via saddle-point dynamics,” in Proc. 21st IFAC World Congress, Berlin, Germany, 2020, pp. 971–976, doi: 10.1016/j.ifacol.2020.12.1261.
    4. J. Venkatasubramanian, J. Köhler, J. Berberich, and F. Allgöwer, “Robust dual control based on gain scheduling,” in Proc. 59th IEEE Conf. Decision and Control (CDC), Jeju, South Korea, 2020, pp. 2270–2277, doi: 10.1109/CDC42340.2020.9304336.
    5. M. Hertneck, S. Linsenmayer, and F. Allgöwer, “Model-Based Nonlinear Periodic Event-Triggered Control for Continuous-Time Systems with Sampled-Data Prediction,” in Proc. European Control Conf. (ECC), Saint Petersburg, Russia, 2020, pp. 1814–1819.
    6. M. Hertneck, S. Linsenmayer, and F. Allgöwer, “Nonlinear Dynamic Periodic Event-Triggered Control with Robustness to Packet Loss Based on Non-Monotonic Lyapunov Functions,” in Proc. 58th IEEE Conf. Decision and Control (CDC), Nice, France, 2019, pp. 1680–1685, doi: 10.1109/CDC40024.2019.9029770.
    7. 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, doi: 10.1109/CCNC.2019.8651811.
    8. 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.
    9. A. Romer, J. M. Montenbruck, and F. Allgöwer, “Determining dissipation inequalities from input-output samples,” in Proc. 20th IFAC World Congress, Toulouse, France, 2017, pp. 7789–7794, doi: 10.1016/j.ifacol.2017.08.1053.
    10. 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.
    11. S. Zeng, H. Ishii, and F. Allgöwer, “State estimation of interconnected ensembles with anonymized outputs,” Tokyo, Japan, 2016.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. T. Schweickhardt, F. Allgöwer, and F. J. Doyle III, “The optimal control law nonlinearity measure: Improving control-relevant nonlinearity assessment,” San Francisco, CA, USA, 2003.
    30. 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.

Frank Allgöwer is director of the Institute for Systems Theory and Automatic Control and professor in Mechanical Engineering at the University of Stuttgart in Germany.

Frank's main interests in research and teaching are in the area of systems and control with a current emphasis on the development of new methods for data-based control, optimiza-tion- based control, networks of systems, and systems biology. Frank received several recogni- tions for his work including 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 of the Deutsche Forschungsgemeinschaft. Frank has been the President of the International Federation of Automatic Control (IFAC) for the years 2017-2020. He was Editor for the journal Automatica from 2001 to 2015 and is editor for the Springer Lecture Notes in Control and Information Science book series and has published over 900 scientific articles. From 2012 until 2020 Frank served a Vice-President of Germany's most important research funding agency the German Research Foundation (DFG).

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