Contact
Pfaffenwaldring 9
70569 Stuttgart
Germany
Room: 2.246
Office Hours
By appointment.
Secretaries:
Yaryna Svyryda: +49 711 685-67736 - yaryna.svyryda@ist.uni-stuttgart.de
Jasmin Winkler: +49 711 685-67731 - jasmin.winkler@ist.uni-stuttgart.de
(Journal-) Articles
- M. Seidel, M. Hertneck, P. Yu, S. Linsenmayer, D. V. Dimarogonas, and F. Allgöwer, “A Window-based Periodic Event-triggered Consensus Scheme for Multi-agent Systems,” IEEE Transactions on Control of Network Systems, vol. 11, no. 1, Art. no. 1, Mar. 2024, doi: 10.1109/tcns.2023.3285863.
- L. Schwenkel, A. Hadorn, M. A. Müller, and F. Allgöwer, “Linearly discounted economic MPC without terminal conditions for periodic optimal operation,” Automatica, vol. 159, p. 111393, 2024, doi: 10.1016/j.automatica.2023.111393.
- M. Köhler, M. A. Müller, and F. Allgöwer, “Distributed MPC for Self-Organized Cooperation of Multi-Agent Systems,” IEEE Transactions on Automatic Control, pp. 1–8, 2024, doi: 10.1109/TAC.2024.3407633.
- R. Strässer, M. Schaller, K. Worthmann, J. Berberich, and F. Allgöwer, “SafEDMD: A certified learning architecture tailored to data-driven control of nonlinear dynamical systems,” submitted, Preprint: arxiv:2402.03145, 2024.
- N. Chatzikiriakos, R. Strässer, F. Allgöwer, and A. Iannelli, “End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data,” submitted, Preprint: arXiv:2409.18010, 2024.
- M. Hertneck and F. Allgöwer, “Robust dynamic self-triggered control for nonlinear systems using hybrid Lyapunov functions,” Nonlinear Analysis: Hybrid Systems, vol. 53, p. 101485, 2024, doi: 10.1016/j.nahs.2024.101485.
- D. Meister, F. Aurzada, M. A. Lifshits, and F. Allgöwer, “Time- versus event-triggered consensus of a single-integrator multi-agent system,” Nonlinear Analysis: Hybrid Systems, vol. 53, p. 101494, 2024, doi: 10.1016/j.nahs.2024.101494.
- D. Meister, D. J. Antunes, and F. Allgöwer, “How improving performance may imply losing consistency in event-triggered consensus,” submitted, 2024, [Online]. Available: https://arxiv.org/abs/2405.03245
- M. Hertneck, S. Lang, J. Berberich, and F. Allgöwer, “Event-Triggered Control Based on Integral Quadratic Constraints,” IEEE Control Systems Letters, vol. 8, pp. 2039–2044, 2024, doi: 10.1109/LCSYS.2024.3427989.
- T. Martin and F. Allgöwer, “Data-Driven System Analysis of Nonlinear Systems Using Polynomial Approximation,” IEEE Transactions on Automatic Control, vol. 69, no. 7, Art. no. 7, 2024, doi: 10.1109/TAC.2023.3321212.
- R. Strässer, J. Berberich, M. Schaller, K. Worthmann, and F. Allgöwer, “Koopman-based control of nonlinear systems with closed-loop guarantees,” submitted, Preprint: arxiv:2411.10359, 2024.
- S. Schlor and F. Allgöwer, “Bootstrapping Guarantees: Stability and Performance Analysis for Dynamic Encrypted Control,” IEEE Control Systems Lett., 2024, doi: 10.1109/LCSYS.2024.3398197.
- R. Strässer, M. Schaller, K. Worthmann, J. Berberich, and F. Allgöwer, “Koopman-based feedback design with stability guarantees,” IEEE Transactions on Automatic Control, pp. 1–16, 2024, doi: 10.1109/TAC.2024.3425770.
- M. Seidel, S. Lang, and F. Allgöwer, “On l2-performance of weakly-hard real-time control systems,” European Journal of Control, p. 101056, Jun. 2024, doi: 10.1016/j.ejcon.2024.101056.
- M. Köhler, M. A. Müller, and F. Allgöwer, “Distributed Economic MPC with Adaptive Terminal Weights,” IFAC-PapersOnLine, vol. 58, no. 18, Art. no. 18, 2024, doi: 10.1016/j.ifacol.2024.09.016.
- J. Venkatasubramanian, J. Köhler, J. Berberich, and F. Allgöwer, “Sequential learning and control: Targeted exploration for robust performance,” IEEE Transactions on Automatic Control, pp. 1–16, 2024, doi: 10.1109/TAC.2024.3430088.
- R. Strässer, S. Schlor, and F. Allgöwer, “Decrypting Nonlinearity: Koopman Interpretation and Analysis of Cryptosystems,” Automatica, Preprint: arxiv:2311.12714, 2024.
- V. Wagner, R. Strässer, F. Allgöwer, and N. E. Radde, “A provably convergent control closure scheme for the Method of Moments of the Chemical Master Equation,” Journal of Chemical Theory and Computation, vol. 19, no. 24, Art. no. 24, Dec. 2023, doi: https://doi.org/10.1021/acs.jctc.3c00548.
- T. Martin, T. B. Schön, and F. Allgöwer, “Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey,” Annual Reviews in Control, vol. 56, p. 100911, 2023, doi: 10.1016/j.arcontrol.2023.100911.
- A. Alanwar, A. Koch, F. Allgöwer, and F. H. Johansson, “Data-Driven Reachability Analysis from Noisy Data,” IEEE Transactions on Automatic Control, pp. 1–16, 2023, doi: 10.1109/TAC.2023.3257167.
- J. Bongard, J. Berberich, J. Köhler, and F. Allgöwer, “Robust stability analysis of a simple data-driven model predictive control approach,” IEEE Trans. Automat. Control, vol. 68, no. 5, Art. no. 5, 2023, doi: 10.1109/TAC.2022.3163110.
- L. Schwenkel, J. Köhler, M. A. Müller, and F. Allgöwer, “Model predictive control for linear uncertain systems using integral quadratic constraints,” IEEE Trans. Automat. Control, vol. 68, no. 1, Art. no. 1, 2023, doi: 10.1109/TAC.2022.3171410.
- P. N. Köhler, M. A. Müller, and F. Allgöwer, “Approximate Dissipativity of Cost-Interconnected Systems in Distributed Economic MPC,” IEEE Transactions on Automatic Control, vol. 68, no. 4, Art. no. 4, 2023, doi: 10.1109/TAC.2022.3173028.
- R. Soloperto, J. Köhler, and F. Allgöwer, “A Nonlinear MPC Scheme for Output Tracking Without Terminal Ingredients,” IEEE Transactions on Automatic Control, vol. 68, no. 4, Art. no. 4, 2023, doi: 10.1109/TAC.2022.3173494.
- 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, vol. 68, no. 5, Art. no. 5, 2023, doi: 10.1109/TAC.2022.3226652.
- J. Berberich, C. W. Scherer, and F. Allgöwer, “Combining prior knowledge and data for robust controller design,” IEEE Trans. Automat. Control, vol. 68, no. 8, Art. no. 8, 2023, doi: 10.1109/TAC.2022.3209342.
- X. Wang, J. Sun, J. Berberich, G. Wang, F. Allgöwer, and J. Chen, “Data-driven Control of Dynamic Event-triggered Systems with Delays,” Int. J. Robust and Nonlinear Control, vol. 33, pp. 7071–7093, 2023, doi: 10.1002/rnc.6740.
- M. Köhler, L. Krügel, L. Grüne, M. A. Müller, and F. Allgöwer, “Transient Performance of MPC for Tracking,” IEEE Control Systems Letters, vol. 7, pp. 2545–2550, 2023, doi: 10.1109/LCSYS.2023.3287798.
- Y. Xie, J. Berberich, and F. Allgöwer, “Linear Data-Driven Economic MPC with Generalized Terminal Constraint,” IFAC World Congress, 2023.
- X. Wang, J. Berberich, J. Sun, G. Wang, F. Allgöwer, and J. Chen, “Model-based and data-driven control of event-and self-triggered discrete-time systems,” IEEE Trans. Cybernetics, vol. 53, no. 9, Art. no. 9, 2023, doi: 10.1109/TCYB.2023.3272216.
- M. Alsalti, V. G. Lopez, J. Berberich, F. Allgöwer, and M. A. Müller, “Data-based control of feedback linearizable systems,” IEEE Trans. Automat. Control, vol. 68, no. 11, Art. no. 11, 2023, doi: 10.1109/TAC.2023.3249289.
- M. Köhler, M. A. Müller, and F. Allgöwer, “Distributed Model Predictive Control for Periodic Cooperation of Multi-Agent Systems,” IFAC-PapersOnLine, vol. 56, no. 2, Art. no. 2, 2023, doi: 10.1016/j.ifacol.2023.10.1450.
- T. Martin and F. Allgöwer, “Data-driven system analysis of nonlinear systems using polynomial approximation,” IEEE Trans. Automat. Control (early access), 2023, doi: 10.1109/TAC.2023.3321212.
- R. Soloperto, M. A. Müller, and F. Allgöwer, “Guaranteed Closed-Loop Learning in Model Predictive Control,” IEEE Transactions on Automatic Control, vol. 68, no. 2, Art. no. 2, 2023, doi: 10.1109/TAC.2022.3172453.
- 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, vol. 67, no. 9, Art. no. 9, 2022, doi: 10.1109/TAC.2022.3166851.
- P. Pauli, J. Berberich, and F. Allgöwer, “Robustness analysis and training of recurrent neural networks using dissipativity theory,” at - Automatisierungstechnik, vol. 70, no. 8, Art. no. 8, 2022, doi: 10.1515/auto-2022-0032.
- C. Klöppelt, J. Berberich, F. Allgöwer, and M. A. Müller, “A novel constraint-tightening approach for robust data-driven predictive control,” Int. J. Robust and Nonlinear Control, 2022, doi: 10.1002/rnc.6532.
- 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, vol. 67, no. 9, Art. no. 9, 2022, doi: 10.1109/TAC.2022.3166872.
- S. Wildhagen, F. Dürr, and F. Allgöwer, “Rollout event-triggered control: reconciling event- and time-triggered control,” at - Automatisierungstechnik, vol. 70, no. 4, Art. no. 4, 2022, doi: 10.1515/auto-2021-0111.
- M. Sharf, A. Koch, D. Zelazo, and F. Allgöwer, “Model-Free Practical Cooperative Control for Diffusively Coupled Systems,” IEEE Transactions on Automatic Control, vol. 67, no. 2, Art. no. 2, 2022, doi: 10.1109/TAC.2021.3056582.
- M. Hertneck, S. Linsenmayer, and F. Allgöwer, “Efficient stability analysis approaches for nonlinear weakly-hard real-time control systems,” Automatica, vol. 133, p. 109868, 2021, doi: https://doi.org/10.1016/j.automatica.2021.109868.
- P. Pauli, A. Koch, J. Berberich, P. Kohler, and F. Allgöwer, “Training Robust Neural Networks using Lipschitz Bounds,” IEEE Control Systems Lett., vol. 6, pp. 121–126, 2021, doi: 10.1109/LCSYS.2021.3050444.
- 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.
- A. Koch, J. M. Montenbruck, and F. Allgöwer, “Sampling Strategies for Data-Driven Inference of Input-Output System Properties,” IEEE Trans. Automat. Control, vol. 66, pp. 1144–1159, 2021, doi: 10.1109/TAC.2020.2994894.
- T. Martin and F. Allgöwer, “Dissipativity verification with guarantees for polynomial systems from noisy input-state data,” IEEE Control Systems Lett., vol. 5, no. 4, Art. no. 4, 2021, doi: 10.1109/LCSYS.2020.3037842.
- J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Data-driven model predictive control with stability and robustness guarantees,” IEEE Trans. Automat. Control, vol. 66, no. 4, Art. no. 4, 2021, doi: 10.1109/TAC.2020.3000182.
- J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Data-driven model predictive control: closed-loop guarantees and experimental results,” at-Automatisierungstechnik, vol. 69, no. 7, Art. no. 7, 2021, doi: 10.1515/auto-2021-0024.
- A. Koch, J. Berberich, J. Köhler, and F. Allgöwer, “Determining optimal input–output properties: A data-driven approach,” Automatica, vol. 134, p. 109906, 2021, doi: https://doi.org/10.1016/j.automatica.2021.109906.
- M. I. Müller, A. Koch, F. Allgöwer, and C. R. Rojas, “Data-Driven Input-Passivity Estimation Using Power Iterations,” IFAC-PapersOnLine, vol. 54, no. 7, Art. no. 7, 2021, doi: https://doi.org/10.1016/j.ifacol.2021.08.429.
- S. Linsenmayer, B. W. Carabelli, S. Wildhagen, K. Rothermel, and F. Allgöwer, “Controller and Triggering Mechanism Co-Design for Control over Time-Slotted Networks,” IEEE Trans.\ Control of Network Systems, vol. 8, no. 1, Art. no. 1, 2021, doi: 10.1109/TCNS.2020.3024316.
- P. Pauli, A. Koch, J. Berberich, P. Kohler, and F. Allgöwer, “Training Robust Neural Networks Using Lipschitz Bounds,” IEEE Control Systems Letters, vol. 6, pp. 121–126, 2021, doi: 10.1109/LCSYS.2021.3050444.
- S. Yu, M. Hirche, Y. Huang, H. Chen, and F. Allgöwer, “Model predictive control for autonomous ground vehicles: a review,” Auton. Intell. Syst., vol. 1, p. 4, 2021, doi: 10.1007/s43684-021-00005-z.
- A. Koch, J. Berberich, and F. Allgöwer, “Provably robust verification of dissipativity properties from data,” IEEE Transactions on Automatic Control, vol. 67, no. 8, Art. no. 8, 2021, doi: 10.1109/TAC.2021.3116179.
- P. Wenzelburger and F. Allgöwer, “Model Predictive Control for Flexible Job Shop Scheduling in Industry 4.0,” Applied Sciences, vol. 11, no. 17, Art. no. 17, 2021, doi: 10.3390/app11178145.
- J. Köhler, L. Schwenkel, A. Koch, J. Berberich, P. Pauli, and F. Allgöwer, “Robust and optimal predictive control of the COVID-19 outbreak,” Annual reviews in Control, 2020.
- J. Köhler, M. A. Müller, and F. Allgöwer, “A nonlinear tracking model predictive control scheme for unreachable dynamic target signals,” Automatica, vol. 118, p. 109030, 2020.
- J. Köhler, M. A. Müller, and F. Allgöwer, “Periodic optimal control of nonlinear constrained systems using economic model predictive control,” J. Proc. Contr., vol. 92, pp. 185–201, 2020.
- R. Soloperto, J. Köhler, and F. Allgöwer, “Augmenting MPC schemes with active learning: Intuitive tuning and guaranteed performance,” IEEE Control Systems Letters, vol. 4, no. 3, Art. no. 3, 2020.
- J. Nubert, J. Köhler, V. Berenz, F. Allgöwer, and S. Trimpe, “Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control,” IEEE Robotics and Automation Letters, vol. 5, no. 2, Art. no. 2, 2020.
- J. Köhler, P. Kötting, R. Soloperto, F. Allgöwer, and M. A. Müller, “A robust adaptive model predictive control framework for nonlinear uncertain systems,” Int. J. Robust and Nonlinear Control, pp. 1–25, 2020.
- J. Köhler, M. A. Müller, and F. Allgöwer, “A nonlinear model predictive control framework using reference generic terminal ingredients,” IEEE Trans. Automat. Control, vol. 65, no. 8, Art. no. 8, 2020.
- K. Kuritz, D. Stöhr, D. S. Maichl, N. Pollak, M. Rehm, and F. Allgöwer, “Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities,” Scientific Reports, vol. 10, no. 1, Art. no. 1, 2020, doi: 10.1038/s41598-020-60400-z.
- J. Berberich, J. Köhler, F. Allgöwer, and M. A. Müller, “Dissipativity properties in constrained optimal control: A computational approach,” Automatica, vol. 114, p. 108840, 2020, doi: 10.1016/j.automatica.2020.108840.
- 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.
- D. Imig, N. Pollak, F. Allgöwer, and M. Rehm, “Sample-based modeling reveals bidirectional interplay between cell cycle progression and extrinsic apoptosis,” PLoS Computational Biology, vol. 16, no. 6, Art. no. 6, 2020.
- S. Wildhagen, M. A. Müller, and F. Allgöwer, “Predictive Control over a Dynamical Token Bucket Network,” IEEE Control Systems Lett., vol. 3, no. 4, Art. no. 4, 2019, doi: 10.1109/LCSYS.2019.2919264.
- A. Romer, J. Berberich, J. Köhler, and F. Allgöwer, “One-shot verification of dissipativity properties from input-output data,” IEEE Control Systems Lett., vol. 3, pp. 709–714, 2019, doi: 10.1109/LCSYS.2019.2917162.
- J. Köhler, M. A. Müller, and F. Allgöwer, “Distributed model predictive control - Recursive feasibility under inexact dual optimization,” Automatica, vol. 102, pp. 1–9, 2019.
- 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.
- 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, doi: 10.1016/j.nahs.2019.05.007.
- 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, doi: 10.1016/j.automatica.2019.04.039.
- 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.
- 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, Art. no. 1112, 2018, doi: 10.1038/s41419-018-1160-2.
- 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, Art. no. 4, 2018, doi: 10.1109/TCNS.2017.2733959.
- 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, Art. no. 6, 2018, doi: https://doi.org/10.1371/journal.pone.0198203.
- 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, Art. no. 19, 2018, doi: https://doi.org/10.1016/j.ifacol.2018.09.028.
- 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, Art. no. 9, 2018.
- J. Köhler, M. A. Müller, and F. Allgöwer, “On periodic dissipativity notions in economic model predictive control,” IEEE Control Systems Letters, vol. 2, no. 3, Art. no. 3, 2018.
- P. N. Köhler, M. A. Müller, and F. Allgöwer, “A distributed economic MPC framework for cooperative control under conflicting objectives,” Automatica, vol. 96, pp. 368–379, 2018, doi: https://doi.org/10.1016/j.automatica.2018.07.001.
- S. Linsenmayer, H. Ishii, and F. Allgöwer, “Containability with event-based sampling for scalar systems with time-varying delay and uncertainty,” IEEE Control Systems Lett., vol. 2, no. 4, Art. no. 4, 2018, doi: 10.1109/lcsys.2018.2847449.
- F. A. Bayer, M. A. Müller, and F. Allgöwer, “On optimal system operation in robust economic MPC,” Automatica, vol. 88, pp. 98–106, 2018, doi: https://doi.org/10.1016/j.automatica.2017.11.007.
- J. Berberich, J. Köhler, F. Allgöwer, and M. A. Müller, “Indefinite Linear Quadratic Optimal Control: Strict Dissipativity and Turnpike Properties,” IEEE Control Systems Lett., vol. 2, no. 3, Art. no. 3, 2018, doi: 10.1109/LCSYS.2018.2842142.
- 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.
- 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, Art. no. 19, 2018, doi: https://doi.org/10.1016/j.ifacol.2018.09.034.
- K. Kuritz, S. Zeng, and F. Allgöwer, “Ensemble Controllability of Cellular Oscillators,” IEEE Control Systems Letters, vol. 3, no. 2, Art. no. 2, 2018, doi: 10.1109/LCSYS.2018.2870967.
- F. D. Brunner, D. Antunes, and F. Allgöwer, “Stochastic thresholds in event-triggered control: A consistent policy for quadratic control,” Automatica, vol. 89, pp. 376–381, 2018.
- M. Lorenzen, F. Dabbene, R. Tempo, and F. Allgöwer, “Stochastic MPC with Offline Uncertainty Sampling,” Automatica, vol. 81, pp. 176–183, 2017, doi: https://doi.org/10.1016/j.automatica.2017.03.031.
- 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, Art. no. 2, 2017.
- G. Goebel and F. Allgöwer, “New results on semi-explicit and almost explicit MPC algorithms,” at-Automatisierungstechnik, vol. 65, no. 4, Art. no. 4, 2017.
- G. Goebel and F. Allgöwer, “Semi-explicit MPC based on subspace clustering,” Automatica, vol. 83, pp. 309–316, 2017.
- 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.
- 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, doi: 10.1016/j.jtbi.2016.11.024.
- M. Lorenzen, F. Dabbene, R. Tempo, and F. Allgöwer, “Constraint-Tightening and Stability in Stochastic Model Predictive Control,” IEEE Trans. Automat. Control, vol. 62, no. 7, Art. no. 7, 2017, doi: 10.1109/TAC.2016.2625048.
- C. Thomaseth, K. Kuritz, F. Allgoewer, and R. N., “The circuit-breaking algorithm for monotone systems,” Mathematical Biosciences, vol. 284, pp. 80–91, 2017.
- M. Lorenzen, M. A. Müller, and F. Allgöwer, “Stochastic Model Predictive Control without Terminal Constraints,” Int. J. Robust and Nonlinear Control, 2017, doi: 10.1002/rnc.3912.
- S. Zeng and F. Allgöwer, “Structured optimal feedback in multi-agent systems: A static output feedback perspective,” Automatica, vol. 76, pp. 214–221, 2017, doi: 10.1016/j.automatica.2016.10.021.
- Y. Liu et al., “Robust nonlinear control approach to nontrivial maneuvers and obstacle avoidance for quadrotor UAV under disturbances,” Robotics and Autonomous Systems, vol. 98, pp. 317–332, 2017.
- J. M. Montenbruck, M. Arcak, and F. Allgöwer, “An Input-Output Framework for Submanifold Stabilization,” IEEE Trans. Automat. Control, vol. 62, no. 10, Art. no. 10, 2017.
- J. M. Montenbruck, D. Zelazo, and F. Allgöwer, “Fekete Points, Formation Control, and the Balancing Problem,” IEEE Trans. Automat. Control, vol. 62, no. 10, Art. no. 10, 2017.
Conferences
- Yifan Xie, Julian Berberich, Frank Allgöwer, “Data-Driven Min-Max MPC for Linear Systems,” 2024, pp. 3184–3189.
Contributions to anthologies
- 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., in Emerging Applications of Control and Systems Theory: A Festschrift in Honor of Mathukumalli Vidyasagar. , Cham: Springer International Publishing, 2018, pp. 1–13. doi: 10.1007/978-3-319-67068-3_1.
Conference papers
- R. Strässer et al., “Collision Avoidance Safety Filter for an Autonomous E-Scooter using Ultrasonic Sensors,” in Proc. 17th IFAC Symposium on Control in Transportation Systems (CTS 2024), in Proc. 17th IFAC Symposium on Control in Transportation Systems (CTS 2024), vol. 58. 2024, pp. 22–28. doi: 10.1016/j.ifacol.2024.07.313.
- M. Hertneck, A. I. Maass, D. Nesić, and F. Allgöwer, “An $L_p$-norm framework for event-triggered control,” in Proc. European Control Conf. (ECC), in Proc. European Control Conf. (ECC). Stockholm, Sweden, 2024, pp. 2818–2824. doi: 10.23919/ECC64448.2024.10591119.
- K. Worthmann, R. Strässer, M. Schaller, J. Berberich, and F. Allgöwer, “Data-driven MPC with terminal conditions in the Koopman framework,” in Proc. 63rd IEEE Conference on Decision and Control (CDC), Preprint: arxiv:2408.12457, in Proc. 63rd IEEE Conference on Decision and Control (CDC), Preprint: arxiv:2408.12457. 2024.
- R. Strässer, J. Berberich, and F. Allgöwer, “Koopman-based control using sum-of-squares optimization: Improved stability guarantees and data efficiency,” in submitted, Preprint: arxiv:2411.03875, in submitted, Preprint: arxiv:2411.03875. 2024.
- J. Venkatasubramanian, J. Köhler, M. Cannon, and F. Allgöwer, “Towards targeted exploration for non-stochastic disturbances,” in Proc. 20th IFAC Symposium on System Identification SYSID 2024, in Proc. 20th IFAC Symposium on System Identification SYSID 2024. 2024.
- H. Schlüter and F. Allgöwer, “Stochastic Model Predictive Control using Initial State and Variance Interpolation,” in Proc. 62nd IEEE Conference on Decision and Control (CDC), in Proc. 62nd IEEE Conference on Decision and Control (CDC). Singapore: IEEE, Dec. 2023. doi: 10.1109/CDC49753.2023.10383711.
- T. Martin, T. B. Schön, and F. Allgöwer, “Gaussian inference for data-driven state-feedback design of nonlinear systems,” in 22nd IFAC World Congress, in 22nd IFAC World Congress. 2023, pp. 4796–4803. doi: doi.org/10.1016/j.ifacol.2023.10.1245.
- R. Strässer, J. Berberich, and F. Allgöwer, “Robust data-driven control for nonlinear systems using the Koopman operator,” in Proc. 22nd IFAC World Congress, in Proc. 22nd IFAC World Congress, vol. 56. 2023, pp. 2257–2262. doi: https://doi.org/10.1016/j.ifacol.2023.10.1190.
- S. Schlor, R. Strässer, and F. Allgöwer, “Koopman interpretation and analysis of a public-key cryptosystem: Diffie-Hellman key exchange,” in Proc. 22nd IFAC World Congress, in Proc. 22nd IFAC World Congress. Yokohama, Japan, 2023, pp. 984–990. doi: 10.1016/j.ifacol.2023.10.1693.
- J. Berberich, A. Iannelli, A. Padoan, J. Coulson, F. Dörfler, and F. Allgöwer, “A quantitative and constructive proof of Willems’ Fundamental Lemma and its implications,” in Proc. American Control Conf. (ACC), in Proc. American Control Conf. (ACC). San Diego, CA, USA, 2023, pp. 4155–4160. doi: 10.23919/ACC55779.2023.10156227.
- M. Hertneck and F. Allgöwer, “Reverse average dwell time constraints enable arbitrary maximum allowable transmission intervals,” in Proc. 12th IFAC Symp. Nonlinear Control Systems (NOLCOS), in Proc. 12th IFAC Symp. Nonlinear Control Systems (NOLCOS). Canberra, Australia, 2023, pp. 379–384. doi: 10.1016/j.ifacol.2023.02.064.
- R. Strässer, J. Berberich, and F. Allgöwer, “Control of bilinear systems using gain-scheduling: Stability and performance guarantees,” in Proc. 62nd IEEE Conference on Decision and Control (CDC), in Proc. 62nd IEEE Conference on Decision and Control (CDC). Singapore, Singapore, 2023, pp. 4674–4681. doi: 10.1109/CDC49753.2023.10384021.
- M. Alsalti, V. G. Lopez, J. Berberich, F. Allgöwer, and M. A. Müller, “Data-driven nonlinear predictive control for feedback linearizable systems,” in Proc. 22nd IFAC World Congress, in Proc. 22nd IFAC World Congress. Yokohama, Japan, 2023, pp. 617–624. doi: 10.1016/j.ifacol.2023.10.1636.
- P. Pauli, D. Gramlich, and F. Allgöwer, “Lipschitz constant estimation for 1D convolutional neural networks,” in Proc. 5th Annual Learning for Dynamics and Control Conf. (L4DC), in Proc. 5th Annual Learning for Dynamics and Control Conf. (L4DC), vol. 211. Philadelphia, PA, USA: PMLR, 2023, pp. 1321--1332.
- D. Meister, F. Dürr, and F. Allgöwer, “Shared Network Effects in Time- versus Event-Triggered Consensus of a Single-Integrator Multi-Agent System,” in 22nd IFAC World Congress, in 22nd IFAC World Congress. Yokohama, Japan, 2023, pp. 5975–5980. doi: 10.1016/j.ifacol.2023.10.636.
- M. Hertneck and F. Allgöwer, “Self-triggered output feedback control for nonlinear networked control systems based on hybrid Lyapunov functions,” in Proc. 22nd IFAC World Congress, in Proc. 22nd IFAC World Congress. Tokyo, Japan, 2023, pp. 5748–5753. doi: 10.1016/j.ifacol.2023.10.165.
- L. Schwenkel, J. Köhler, M. A. Müller, and F. Allgöwer, “Robust peak-to-peak gain analysis using integral quadratic constraints,” in Proc. 22nd IFAC World Congress, in Proc. 22nd IFAC World Congress. Yokohama, Japan, 2023, pp. 11564–11569. doi: 10.1016/j.ifacol.2023.10.452.
- D. Meister and F. Allgöwer, “Performance implications of different p-norms in level-triggered sampling,” in Proc. 62nd IEEE Conf. on Decision and Control (CDC), in Proc. 62nd IEEE Conf. on Decision and Control (CDC). Singapore, Singapore, 2023, pp. 3878–3883. doi: 10.1109/CDC49753.2023.10384009.
- D. Antunes, D. Meister, T. Namerikawa, F. Allgöwer, and W. P. M. H. Heemels, “Consistent event-triggered consensus on complete graphs,” in Proc. 62nd IEEE Conf. on Decision and Control (CDC), in Proc. 62nd IEEE Conf. on Decision and Control (CDC). Singapore, Singapore, 2023, pp. 3911–3916. doi: 10.1109/CDC49753.2023.10384026.
- Z. Ma, H. Schlüter, F. Berkel, T. Specker, and F. Allgöwer, “Recursive Feasibility and Stability for Stochastic MPC based on Polynomial Chaos,” in Proc. 12th IFAC Symp. Nonlinear Control Systems (NOLCOS), in Proc. 12th IFAC Symp. Nonlinear Control Systems (NOLCOS), vol. 56. Canberra, Australia: Elsevier, Jan. 2023, pp. 204–209. doi: 10.1016/j.ifacol.2023.02.035.
- T. Martin and F. Allgöwer, “Determining dissipativity for nonlinear systems from noisy data using Taylor polynomial approximation,” in Proc. American Control Conf. (ACC), in Proc. American Control Conf. (ACC). Atlanta, GA, USA, 2022, pp. 1432–1437. doi: 10.23919/ACC53348.2022.9867806.
- D. Meister, F. Aurzada, M. A. Lifshits, and F. Allgöwer, “Analysis of Time- versus Event-Triggered Consensus for a Single-Integrator Multi-Agent System,” in Proc. 61st IEEE Conf. on Decision and Control (CDC), in Proc. 61st IEEE Conf. on Decision and Control (CDC). Cancun, Mexico, 2022, pp. 441–446. doi: 10.1109/CDC51059.2022.9993301.
- M. Köhler, J. Berberich, M. A. Müller, and F. Allgöwer, “Data-driven distributed MPC of dynamically coupled linear systems,” in Proc. 25th Int. Symp. Math. Theory Netw. Syst. (MTNS), in Proc. 25th Int. Symp. Math. Theory Netw. Syst. (MTNS). Bayreuth, Germany, 2022, pp. 365–370. doi: 10.1016/j.ifacol.2022.11.080.
- H. Schlüter and F. Allgöwer, “Stochastic model predictive control using initial state optimization,” in Proc. 25th Int. Symp. Mathematical Theory of Networks and Systems (MTNS), in Proc. 25th Int. Symp. Mathematical Theory of Networks and Systems (MTNS), vol. 55. Bayreuth, Germany: Elsevier, Nov. 2022, pp. 454–459. doi: 10.1016/j.ifacol.2022.11.095.
- P. Pauli, N. Funcke, D. Gramlich, M. A. Msalmi, and F. Allgöwer, “Neural network training under semidefinite constraints,” in 2022 IEEE 61st Conference on Decision and Control (CDC), in 2022 IEEE 61st Conference on Decision and Control (CDC). Dec. 2022, pp. 2731–2736. doi: 10.1109/CDC51059.2022.9992331.
- M. Hertneck and F. Allgöwer, “Dynamic self-triggered control for nonlinear systems with delays,” in Proc. 9th IFAC Conf. on Networked Systems (NECSYS), in Proc. 9th IFAC Conf. on Networked Systems (NECSYS). Zürich, Switzerland, 2022, pp. 312–317. doi: 10.1016/j.ifacol.2022.07.278.
- S. Wildhagen, M. Pezzutto, L. Schenato, and F. Allgöwer, “Self-triggered MPC robust to bounded packet loss via a min-max approach,” in 2022 IEEE 61st Conference on Decision and Control (CDC), in 2022 IEEE 61st Conference on Decision and Control (CDC). 2022, pp. 7670–7675. doi: 10.1109/CDC51059.2022.9992581.
- R. Drummond, S. Duncan, M. Turner, P. Pauli, and F. Allgower, “Bounding the difference between model predictive control and neural networks,” in Learning for Dynamics and Control Conference, in Learning for Dynamics and Control Conference. PMLR, 2022, pp. 817--829.
- D. Müller, J. Feilhauer, J. Wickert, J. Berberich, F. Allgöwer, and O. Sawodny, “Data-driven predictive disturbance observer for quasi continuum manipulators,” in Proc. 61st IEEE Conf. Decision and Control (CDC), in Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, pp. 1816–1822. doi: 10.1109/CDC51059.2022.9992740.
- J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Stability in data-driven MPC: an inherent robustness perspective,” in Proc. 61st IEEE Conf. Decision and Control (CDC), in Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, pp. 1105–1110. doi: 10.1109/CDC51059.2022.9993361.
- P. Pauli, D. Gramlich, J. Berberich, and F. Allgöwer, “Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers,” in Proc. 60th IEEE Conf. on Decision and Control (CDC), in Proc. 60th IEEE Conf. on Decision and Control (CDC). Austin, TX, USA, 2021, pp. 3611–3618.
- P. Pauli, J. Köhler, J. Berberich, A. Koch, and F. Allgöwer, “Offset-free setpoint tracking using neural network controllers,” in Proc. 3rd Conf. on Learning for Dynamics and Control (L4DC), in Proc. 3rd Conf. on Learning for Dynamics and Control (L4DC). Zurich, Switzerland, 2021, pp. 992–1003.
- A. Alanwar, A. Koch, F. Allgöwer, and K. H. Johansson, “Data-Driven Reachability Analysis Using Matrix Zonotopes,” in Proceedings of the 3rd Conference on Learning for Dynamics and Control, in Proceedings of the 3rd Conference on Learning for Dynamics and Control, vol. 144. 2021, pp. 163--175.
- M. Hertneck and F. Allgöwer, “A Simple Approach to Increase the Maximum Allowable Transmission Interval,” in Proc. 3rd IFAC Conf. on Modelling, Identification and Control of Nonlinear Systems (MICNON), in Proc. 3rd IFAC Conf. on Modelling, Identification and Control of Nonlinear Systems (MICNON). Tokyo, Japan, 2021, pp. 443–448. doi: 10.1016/j.ifacol.2021.10.390.
- N. Wieler, J. Berberich, A. Koch, and F. Allgöwer, “Data-Driven Controller Design via Finite-Horizon Dissipativity,” in Proceedings of the 3rd Conference on Learning for Dynamics and Control, in Proceedings of the 3rd Conference on Learning for Dynamics and Control, vol. 144. PMLR, 2021, pp. 287--298.
- J. Berberich, S. Wildhagen, M. Hertneck, and F. Allgöwer, “Data-driven analysis and control of continuous-time systems under aperiodic sampling,” in Proc. 19th IFAC Symp. System Identification (SYSID), in Proc. 19th IFAC Symp. System Identification (SYSID). Padova, Italy, 2021, pp. 210–215. doi: 10.1016/j.ifacol.2021.08.360.
- R. Soloperto, P. Wenzelburger, D. Meister, D. Scheuble, V. S. M. Breidohr, and F. Allgöwer, “A control framework for autonomous e-scooters,” in Proc. 16th IFAC Symposium on Control in Transportation Systems (CTS), in Proc. 16th IFAC Symposium on Control in Transportation Systems (CTS). Lille, France, 2021, pp. 252–258. doi: 10.1016/j.ifacol.2021.06.030.
- C. Klöppelt, L. Schwenkel, F. Allgöwer, and M. A. Müller, “Transient Performance of Tube-based Robust Economic Model Predictive Control,” in Proc. IFAC Conf. Nonlinear Model Predictive Control (NMPC), in Proc. IFAC Conf. Nonlinear Model Predictive Control (NMPC). Bratislava, Slovakia, 2021, pp. 28–35. doi: 10.1016/j.ifacol.2021.08.520.
- J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “On the design of terminal ingredients for data-driven MPC,” in Proc. 7th IFAC Conf. Nonlinear Model Predictive Control (NMPC), in Proc. 7th IFAC Conf. Nonlinear Model Predictive Control (NMPC). Bratislava, Slovakia, 2021, pp. 257–263. doi: 10.1016/j.ifacol.2021.08.554.
- M. Alsalti, J. Berberich, V. G. Lopez, F. Allgöwer, and M. A. Müller, “Data-Based System Analysis and Control of Flat Nonlinear Systems,” in Proc. 60th IEEE Conf. Decision and Control (CDC), in Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, pp. 1484–1489. doi: 10.1109/CDC45484.2021.9683327.
- M. Hertneck and F. Allgöwer, “Dynamic self-triggered control for nonlinear systems based on hybrid Lyapunov functions,” in Proc. 60th IEEE Conf. Decision and Control (CDC), in Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, pp. 533–539. doi: 10.1109/CDC45484.2021.9682784.
- S. Schlor, M. Hertneck, S. Wildhagen, and F. Allgöwer, “Multi-party computation enables secure polynomial control based solely on secret-sharing,” in Proc. 60th IEEE Conf. Decision and Control (CDC), in Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, pp. 4882–4887. doi: 10.1109/CDC45484.2021.9683026.
- S. Wildhagen, J. Berberich, M. Hirche, and F. Allgöwer, “Improved stability conditions for systems under aperiodic sampling: model- and data-based analysis,” in Proc. 60th IEEE Conf. on Decision and Control (CDC), in Proc. 60th IEEE Conf. on Decision and Control (CDC). Austin, TX, USA, 2021, pp. 5788–5794.
- R. Strässer, J. Berberich, and F. Allgöwer, “Data-Driven Control of Nonlinear Systems: Beyond Polynomial Dynamics,” in Proc. 60th IEEE Conf. Decision and Control (CDC), in Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, pp. 4344–4351. doi: 10.1109/CDC45484.2021.9683211.
- J. Venkatasubramanian, J. Köhler, J. Berberich, and F. Allgöwer, “Robust dual control based on gain scheduling,” in 2020 59th IEEE Conference on Decision and Control (CDC), in 2020 59th IEEE Conference on Decision and Control (CDC). IEEE, 2021, pp. 2270–2277. doi: 10.1109/CDC42340.2020.9304336.
- E. Müller, P. N. Köhler, K. Y. Pettersen, and F. Allgöwer, “Economic model predictive control for obstacle-aided snake robot locomotion,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020.
- P. Pauli, A. Koch, and F. Allgöwer, “Smartphone Apps for Learning Progress and Course Revision,” in Proc.\ 21st IFAC World Congress, in Proc.\ 21st IFAC World Congress. Berlin, Germany, Jul. 2020.
- D. Persson, A. Koch, and F. Allgöwer, “Probabilistic H2-norm estimation via Gaussian process system identification,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020, pp. 431–436. doi: 10.1016/j.ifacol.2020.12.211.
- J. Berberich, A. Koch, C. W. Scherer, and F. Allgöwer, “Robust data-driven state-feedback design,” in Proc. American Control Conf. (ACC), in Proc. American Control Conf. (ACC). Denver, CO, USA, 2020, pp. 1532–1538. doi: 10.23919/ACC45564.2020.9147320.
- S. Wildhagen and F. Allgöwer, “Scheduling and control over networks using MPC with time-varying terminal ingredients,” in Proc. American Control Conf. (ACC), in Proc. American Control Conf. (ACC). Denver, CO, USA, 2020, pp. 1913–1918. doi: 10.23919/ACC45564.2020.9147411.
- 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), in Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, pp. 2270–2277. doi: 10.1109/CDC42340.2020.9304336.
- M. Hertneck, S. Linsenmayer, and F. Allgöwer, “Stabilization of Nonlinear Weakly Hard Real-Time Control Systems,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020, pp. 2632–2637. doi: 10.1016/j.ifacol.2020.12.307.
- S. Wildhagen and F. Allgöwer, “Rollout scheduling and control for disturbed systems via tube MPC,” in Proc. 59th IEEE Conf. Decision and Control (CDC), in Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, pp. 3145–3150. doi: 10.1109/CDC42340.2020.9304512.
- J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Robust constraint satisfaction in data-driven MPC,” in Proc. 59th IEEE Conf. Decision and Control (CDC), in Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, pp. 1260–1267. doi: 10.1109/CDC42340.2020.9303965.
- M. Hirche, P. N. Köhler, M. A. Müller, and F. Allgöwer, “Distributed Model Predictive Control for Consensus of Constrained Heterogeneous Linear Systems,” in Proc. 59th IEEE Conf. on Decision and Control (CDC), in Proc. 59th IEEE Conf. on Decision and Control (CDC). Jeju Island, Republic of Korea, 2020, pp. 1248–1253. doi: 10.1109/CDC42340.2020.9303838.
- 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), in Proc. European Control Conf. (ECC). Saint Petersburg, Russia, 2020, pp. 1814–1819. doi: 10.1109/CDC40024.2019.9029770.
- A. Koch, J. Berberich, and F. Allgöwer, “Verifying dissipativity properties from noise-corrupted input-state data,” in Proc. 59th IEEE Conf. on Decision and Control (CDC), in Proc. 59th IEEE Conf. on Decision and Control (CDC). Jeju, South Korea, 2020, pp. 616–621. doi: 10.1109/CDC42340.2020.9304380.
- A. Camisa, P. N. Köhler, M. A. Müller, G. Notarstefano, and F. Allgöwer, “A distributed optimization algorithm for Nash bargaining in multi-agent systems,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020.
- J. Berberich and F. Allgöwer, “A trajectory-based framework for data-driven system analysis and control,” in Proc. European Control Conf. (ECC), in Proc. European Control Conf. (ECC). Saint Petersburg, Russia, 2020, pp. 1365–1370. doi: 10.23919/ECC51009.2020.9143608.
- L. Schwenkel, J. Köhler, M. A. Müller, and F. Allgöwer, “Dynamic uncertainties in model predictive control: Guaranteed stability for constrained linear systems,” in 59th IEEE Conference on Decision and Control (CDC), in 59th IEEE Conference on Decision and Control (CDC). 2020, pp. 1235–1241. doi: 10.1109/CDC42340.2020.9303819.
- L. Schwenkel, J. Köhler, M. A. Müller, and F. Allgöwer, “Robust Economic Model Predictive Control without Terminal Conditions,” in Proc. of 21st IFAC World Congress, in Proc. of 21st IFAC World Congress. 2020. doi: 10.1016/j.ifacol.2020.12.465.
- M. Hertneck, S. Linsenmayer, and F. Allgöwer, “Stability Analysis for Nonlinear Weakly Hard Real-Time Control Systems,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020, pp. 2632–2637. doi: 10.1016/j.ifacol.2020.12.307.
- A. Koch, M. Lorenzen, P. Pauli, and F. Allgöwer, “Facilitating learning progress in a first control course via Matlab apps,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020, pp. 17356–17361. doi: 10.1016/j.ifacol.2020.12.2086.
- T. Martin, A. Koch, and F. Allgöwer, “Data-driven surrogate models for LTI systems via saddle-point dynamics,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020, pp. 971–976. doi: 10.1016/j.ifacol.2020.12.1261.
- J. Köhler, M. A. Müller, and F. Allgöwer, “Implicit solutions to constrained nonlinear output regulation using MPC,” in Proc.\ 59th IEEE Conf.\ Decision and Control (CDC), in Proc.\ 59th IEEE Conf.\ Decision and Control (CDC). 2020, pp. 4604–4609.
- F. Jaumann, S. Wildhagen, and F. Allgöwer, “Saving Tokens in Rollout Control with Token Bucket Specification,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020, pp. 2662–2669. doi: 10.1016/j.ifacol.2020.12.313.
- T. Martin and F. Allgöwer, “Iterative data-driven inference of nonlinearity measures via successive graph approximation,” in Proc. 59th IEEE Conf. Decision and Control (CDC), in Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, pp. 4760–4765. doi: 10.1109/CDC42340.2020.9304285.
- Y. Lian, S. Wildhagen, Y. Jiang, B. Houska, F. Allgöwer, and C. N. Jones, “Resource-Aware Asynchronous Multi-Agent Coordination Via Self-Triggered MPC,” in 59th IEEE Conf. Decision and Control (CDC), in 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, pp. 685–690. doi: 10.1109/CDC42340.2020.9304137.
- J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, “Data-driven tracking MPC for changing setpoints,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020, pp. 971–976. doi: 10.1016/j.ifacol.2020.12.389.
- M. Rosenfelder, J. Köhler, and F. Allgöwer, “Stability and performance in transient average constrained economic MPC without terminal constraints,” in Proc.\ 21st IFAC World Congress, in Proc.\ 21st IFAC World Congress. 2020.
- P. Wenzelburger and F. Allgöwer, “A first step towards an autonomously driving E-Scooter,” in Demonstrator Session 21st IFAC World Congress, in Demonstrator Session 21st IFAC World Congress. Berlin, Germany, 2020. [Online]. Available: https://www.ist.uni-stuttgart.de/institute/team/pdf/PW/IFAC20_E-Scooter.pdf
- H. Schlüter and F. Allgöwer, “A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control under General Bounded Disturbances,” in Proc.\ 21th IFAC World Congress, in Proc.\ 21th IFAC World Congress. Berlin, Germany, Jul. 2020, pp. 7130–7135. doi: 10.1016/j.ifacol.2020.12.518.
- M. Hertneck and F. Allgöwer, “Exploiting Information for Decentralized Periodic Event-Triggered Control,” in Proc. 59th IEEE Conf. Decision and Control (CDC), in Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, pp. 4999–5004. doi: 10.1109/CDC42340.2020.9304456.
- S. Wildhagen, C. N. Jones, and F. Allgöwer, “A resource-aware approach to self-triggered model predictive control,” in Proc. 21st IFAC World Congress, in Proc. 21st IFAC World Congress. Berlin, Germany, 2020. doi: 10.1016/j.ifacol.2020.12.926.
- T. Martin, P. N. Köhler, and F. Allgöwer, “Dissipativity and Economic Model Predictive Control for Optimal Set Operation,” in Proc. American Control Conf. (ACC), in Proc. American Control Conf. (ACC). Philadelphia, PA, USA, 2019, pp. 1020–1026. doi: 10.23919/ACC.2019.8814305.
- R. Soloperto, J. Köhler, M. A. Müller, and F. Allgöwer, “Dual Adaptive MPC for output tracking of linear systems,” in Proc. 58th Conference on Decision and Control (CDC), in Proc. 58th Conference on Decision and Control (CDC). Nice, France, 2019.
- J. Köhler, M. A. Müller, and F. Allgöwer, “A simple framework for nonlinear robust output-feedback MPC,” in Proc. 18th European Control Conference (ECC), in Proc. 18th European Control Conference (ECC). Naples, Italy, 2019, pp. 793–798.
- J. Köhler, E. Andina, R. Soloperto, M. A. Müller, and F. Allgöwer, “Linear robust adaptive model predictive control: Computational complexity and conservatism,” in Proc. 58th IEEE Conference on Decision and Control (CDC), in Proc. 58th IEEE Conference on Decision and Control (CDC). Nice, France, 2019, pp. 1383–1388.
- S. Wildhagen, M. A. Müller, and F. Allgöwer, “Economic MPC using a Cyclic Horizon with Application to Networked Control Systems,” in Proc. 11th IFAC Symp. Nonlinear Control Systems (NOLCOS), in Proc. 11th IFAC Symp. Nonlinear Control Systems (NOLCOS). Vienna, Austria, 2019, pp. 796–801. doi: 10.1016/j.ifacol.2019.12.011.
- 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), in Proc. 58th IEEE Conf. Decision and Control (CDC). Nice, France, 2019, pp. 1680–1685. doi: 10.1109/CDC40024.2019.9029770.
- P. N. Köhler, M. A. Müller, and F. Allgöwer, “Graph topology and subsystem centrality in approximately dissipative system interconnections,” in Proc. 58th IEEE Conference on Decision and Control (CDC), in Proc. 58th IEEE Conference on Decision and Control (CDC). Nice, France, 2019, pp. 7441–7447.
- J. Berberich, M. Sznaier, and F. Allgöwer, “Signal estimation and system identification with nonlinear dynamic sensors,” in 3rd IEEE Conf. Control Technology and Applications (CCTA), in 3rd IEEE Conf. Control Technology and Applications (CCTA). Hong Kong, China, 2019, pp. 505–510. doi: 10.1109/CCTA.2019.8920592.
- P. Wenzelburger and F. Allgöwer, “A Petri Net Modeling Framework for the Control of Flexible Manufacturing Systems,” in Proc. 9th IFAC Conf. Manufacturing Modeling, Management, and Control (MIM), in Proc. 9th IFAC Conf. Manufacturing Modeling, Management, and Control (MIM). Berlin, Germany, 2019, pp. 492–498. doi: 10.1016/j.ifacol.2019.11.111.
- T. Martin and F. Allgöwer, “Nonlinearity Measures for Data-Driven System Analysis and Control,” in Proc. 58th IEEE Conf. Decision and Control (CDC), in Proc. 58th IEEE Conf. Decision and Control (CDC). Nice, France, 2019, pp. 3605–3610. doi: 10.1109/CDC40024.2019.9029804.
- P. Wenzelburger and F. Allgöwer, “A Novel Optimal Online Scheduling Scheme for Flexible Manufacturing Systems,” in Proc. 13th IFAC Workshop on Intelligent Manufacturing Systems (IMS), in Proc. 13th IFAC Workshop on Intelligent Manufacturing Systems (IMS). Oshawa, Canada, 2019, pp. 1–6. doi: 10.1016/j.ifacol.2019.10.002.
- S. Linsenmayer, M. A. Müller, H. Ishii, and F. Allgöwer, “Event-based Containability for Linear Systems with Arbitrarily Small Bit Rates,” in Proc. 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), in Proc. 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys). Chicago, IL, USA, 2019, pp. 31–36. doi: 10.1016/j.ifacol.2019.12.138.
- P. N. Köhler, M. A. Müller, and F. Allgöwer, “Approximate dissipativity and performance bounds for interconnected systems,” in Proc. 18th European Control Conference (ECC), in Proc. 18th European Control Conference (ECC). Naples, Italy, 2019, pp. 787–792.
- A. Romer, S. Trimpe, and F. Allgöwer, “Data-driven inference of passivity properties via Gaussian process optimization,” in Proc. European Control Conf. (ECC), in Proc. European Control Conf. (ECC). Naples, Italy, 2019, pp. 29–35. doi: 10.23919/ECC.2019.8795728.
- 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), in Proc. 16th IEEE Annual Consumer Communications Networking Conf. (CCNC). Las Vegas, NV, USA, 2019, pp. 1–6. doi: 10.1109/CCNC.2019.8651811.
- W. Halter, S. Michalowsky, and F. Allgöwer, “Extremum seeking for optimal enzyme production under cellular fitness constraints,” in Proc. European Control Conf. (ECC), in Proc. European Control Conf. (ECC). Neapel, Italien, 2019.
- M. Nonhoff, P. N. Köhler, and F. Allgöwer, “Economic model predictive control for snake robot locomotion,” in Proc. 58th IEEE Conference on Decision and Control (CDC), in Proc. 58th IEEE Conference on Decision and Control (CDC). Nice, France, 2019.
- R. Soloperto, J. Köhler, M. A. Müller, and F. Allgöwer, “Collision avoidance for uncertain nonlinear systems and moving obstacles using robust Model Predictive Control,” in Proc. 18th European Control Conference (ECC), in Proc. 18th European Control Conference (ECC). Naples, Italy, 2019.
- A. Romer, J. M. Montenbruck, and F. Allgöwer, “Some ideas on sampling strategies for data-driven inference of passivity properties for MIMO systems,” in Proc. American Control Conference (ACC), in Proc. American Control Conference (ACC). Milwaukee, Wisconsin, USA, 2018, pp. 6094–6100. doi: 10.23919/ACC.2018.8431399.
- A. Romer, J. M. Montenbruck, and F. Allgöwer, “Data-driven inference of conic relations via saddle-point dynamics,” in Proc. 9th IFAC Symp. Robust Control Design (ROCOND), in Proc. 9th IFAC Symp. Robust Control Design (ROCOND). Florianópolis, Brazil, 2018, pp. 586–591. doi: 10.1016/j.ifacol.2018.11.139.
- 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), in Proc. 57th IEEE Conf. Decision and Control (CDC). Miami Beach, USA, 2018.
- 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), in Proc. IFAC Conf. Nonlinear Model Predictive Control (NMPC). Madison, Wisconsin, 2018, pp. 656–661.
- S. Linsenmayer and F. Allgöwer, “Performance oriented triggering mechanisms with guaranteed traffic characterization for linear discrete-time systems,” in Proc. European Control Conf. (ECC), in Proc. European Control Conf. (ECC). Limassol, Cyprus, 2018, pp. 1474–1479. doi: 10.23919/ECC.2018.8550568.
- J. Köhler, M. A. Müller, and F. Allgöwer, “Nonlinear Reference Tracking with Model Predictive Control: An Intuitive Approach,” in Proc. European Control Conf. (ECC), in Proc. European Control Conf. (ECC). 2018, pp. 1355–1360.
- 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), in Proc. American Control Conf.(ACC). Milwaukee, Wisconsin, 2018, pp. 1546–1551.
- R. Soloperto, M. A. Müller, and F. Allgöwer, “Learning-Based Robust Model Predictive Control with State-Dependent Uncertainty,” in Proc. 6th IFAC Conference on Nonlinear Model Predictive Control, in Proc. 6th IFAC Conference on Nonlinear Model Predictive Control. Madison, Wisconsin, 2018.
- 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), in Proc. American Control Conf. (ACC). 2018, pp. 728–734.
- 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, in Proc. 6th IFAC Conference on Nonlinear Model Predictive Control. Madison, Wisconsin, 2018, pp. 88–93.
- J. M. Montenbruck and F. Allgöwer, “Separable matrices and minimum complexity controllers,” in Proc. 56th IEEE Conf. Decision and Control (CDC), in Proc. 56th IEEE Conf. Decision and Control (CDC). 2017, pp. 4187–4192.
- A. Romer, J. M. Montenbruck, and F. Allgöwer, “Sampling strategies for data-driven inference of passivity properties,” in Proc. 56th IEEE Conf. Decision and Control (CDC), in Proc. 56th IEEE Conf. Decision and Control (CDC). Melbourne, Victoria, Australia, 2017, pp. 6389–6394. doi: 10.1109/CDC.2017.8264623.
- S. Zeng, J. M. Montenbruck, and F. Allgöwer, “Periodic Signal Compressors,” in Proc. 20th World Congress of the International Federation of Automatic Control, in Proc. 20th World Congress of the International Federation of Automatic Control. 2017, pp. 6649–6654.
- 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), in Proc. 56th IEEE Conf. Decision and Control (CDC). Melbourne, Victoria, Australia, 2017, pp. 6340–6345.
- W. Halter, Z. A. Tuza, and F. Allgöwer, “Signal differentiation with genetic networks,” in Proc. 20th IFAC World Congress, in Proc. 20th IFAC World Congress. Toulouse, France, 2017.
- M. Lorenzen, F. Allgöwer, and M. Cannon, “Adaptive Model Predictive Control with Robust Constraint Satisfaction,” in Proc. 20th IFAC World Congress, in Proc. 20th IFAC World Congress. Toulouse, France, 2017, pp. 3368–3373.
- 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), in Proc. 56th IEEE Conf. Decision and Control (CDC). Melbourne, Victoria, Australia, 2017, pp. 5557–5562.
- S. Linsenmayer, R. Blind, and F. Allgöwer, “Delay-dependent data rate bounds for containability of scalar systems,” in Proc. 20th IFAC World Congress, in Proc. 20th IFAC World Congress. Toulouse, France, 2017, pp. 7875–7880. doi: 10.1016/j.ifacol.2017.08.742.
- 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), in Proc. 56th IEEE Conf. Decision and Control (CDC). Melbourne, Australia, 2017, pp. 4765–4770. doi: 10.1109/CDC.2017.8264364.
- J. M. Montenbruck, S. Zeng, and F. Allgöwer, “Linear Systems with Quadratic Outputs,” in Proc. American Control Conf. (ACC), in Proc. American Control Conf. (ACC). Seattle, WA, USA, 2017, pp. 1030–1034.
- W. Halter, J. M. Montenbruck, and F. Allgöwer, “Systems with integral resource consumption,” in Proc. 56th IEEE Conf. Decision and Control (CDC), in Proc. 56th IEEE Conf. Decision and Control (CDC). Melbourne, Australia, 2017.
- P. N. Köhler, M. A. Müller, J. Pannek, and F. Allgöwer, “On Exploitation of Supply Chain Properties by Sequential Distributed MPC.,” in Proc. 20th IFAC World Congress, in Proc. 20th IFAC World Congress. Toulouse, France, 2017, pp. 8219–8224.
- M. Lorenzen, M. A. Müller, and F. Allgöwer, “Stabilizing Stochastic MPC without Terminal Constraints,” in Proc. American Control Conf. (ACC), in Proc. American Control Conf. (ACC). Seattle, Washington, 2017, pp. 5636–5641.
- A. Romer, J. M. Montenbruck, and F. Allgöwer, “Determining dissipation inequalities from input-output samples,” in Proc. 20th IFAC World Congress, in Proc. 20th IFAC World Congress. Toulouse, France, 2017, pp. 7789–7794. doi: 10.1016/j.ifacol.2017.08.1053.
Preprints
- L. Schwenkel, D. Briem, M. A. Müller, and F. Allgöwer, “On discount functions for economic model predictive control without terminal conditions,” arXiv preprint arXiv:2405.14361, 2024.
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, optimization-based control, networks of systems, and systems biology. Frank received several recognitions 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).
1981 – 1987 Diploma studies in Engineering Cybernetics and Applied
Mathematics at University of Stuttgart and University of California
at Los Angeles (UCLA)
1988 – 1995 Research Associate at Institute for System Dynamics and
Automatic Control, University of Stuttgart
1991 – 1992 Visiting Research Associate, California Institute of Technology,
Pasadena, CA, USA
1995 – 1996 Visiting Research Associate, DuPont Experimental Station,
Wilmington, DE, USA
1996 Ph.D., University of Stuttgart, advisor: Prof. E.D. Gilles
1996 Offer of University of California at Berkeley (tenure-track assistant
professorship)
1996 – 1999 Assistant Professor for Nonlinear Systems, Electrical Engineering
Department, ETH Zürich, Switzerland
1998 Offer of University of Duisburg (Full Professor of Automatic
Control)
1999 Offer of ETH Zürich (Full Professor of Automatic Control)
since 1999 Full Professor and Director of the Institute for Systems Theory
and Automatic Control, University of Stuttgart
2003 – 2004 Visiting Professor, University of California at Santa Barbara, CA,
USA
2007 Offer of University of California at Santa Barbara (Endowed Chair,
Electrical Engineering)
2010 – 2011 Visiting Professor, University of Newcastle, Australia
2012 – 2020 Vice-president of the German Research Foundation (DFG)
2018 Co-founder, Spin-off company TGU Systemwissenschaften
2019 Co-founder, Spin-off company eStarling.io
2002 NaT-Working Award of the Robert Bosch Foundation
2004 Gottfried-Wilhelm-Leibniz Prize of the German Research Foundation
2005 Best Paper Award 2004/2005, Asian Journal of Control
2005 D.B. Robinson Distinguished Speaker (September 29, 2005), University
of Alberta, Edmonton
2006 IEEE Distinguished Lecturer
2006 Fellow, International Federation of Automatic Control (IFAC)
2007 State Teaching Award of the state of Baden-Württemberg
2008 Best Paper Award, Journal Control Engineering Practice
2009 Best Poster Award, Cancer Systems Biology 2009
2011 Best Paper Award, 8th International Workshop on Computational
Systems Biology
2011 Outstanding Service Award, International Federation of Automatic Control
2011 International Best Paper Award, SICE 2011
2013 Best Paper Award 2012/2013, Asian Journal of Control
2013 DeGruyter Publishing Best Paper Award
2015 Distinguished Member Award of the IEEE Control System Society
2017 Journal of Process Control Paper Prize Award
2017 24th Roger Sargent Lecture, December 9, 2017, Imperial College London
2018 Publication Prize 2017, University of Stuttgart
2018 Best Paper Award, 9th IFAC Symposium on Robust Control Design
2019 Best Paper Award, 8th IFAC Workshop on Distributed Estimation and
Control in Networked Systems (NecSys 2019)
2019 Winner „Ideenwettbewerb: Mobilitätskonzepte für den emissionsfreien
Campus“ MWK Baden-Württemberg for the initiative Mobility Living Lab
(MobiLab)
2020 Outstanding Student Paper Award for "Robust Constraint Satisfaction in
Data-Driven MPC" (J. Berberich, J. Köhler, M.A. Müller and F. Allgöwer)
at the IEEE CDC Conference 2020.
2021 Publication Prize 2019, University of Stuttgart
More than 20 invitations for plenary and keynote talks at international conferences in the past five years
Winter term 2021/2022
- Einführung in die Regelungstechnik
- Konzepte der Regelungstechnik (3V/1Ü)
- Praktikum Konzepte der Regelungstechnik
- Matlab Einführungskurs
Summer term 2021
- Projektwettbewerb: Konzepte der Regelungstechnik
- Projektwettbewerb: Einführung in die Regelungstechnik
- Proseminar Technische Kybernetik 2021
- Praktikum: Einführung in die Regelungstechnik
- Mehrgrößenregelung
- Systemdynamische Grundlagen der Regelungstechnik
- Model Predictive Control
- Nonlinear Control
Name |
School |
Year |
Descendants |
Berberich, Julian |
Universität Stuttgart |
2022 |
|
Wenzelburger, Philipp |
Universität Stuttgart |
2022 |
|
Universität Stuttgart |
2021 |
|
|
Universität Stuttgart |
2021 |
||
Löhning, Martin |
Universität Stuttgart |
2021 |
|
Universität Stuttgart |
2020 |
|
|
Universität Stuttgart |
2020 |
|
|
Universität Stuttgart |
2020 |
|
|
Universität Stuttgart |
2020 |
|
|
Universität Stuttgart |
2018 |
|
|
Universität Stuttgart |
2017 |
|
|
Universität Stuttgart |
2017 |
|
|
Universität Stuttgart |
2017 |
|
|
Universität Stuttgart |
2017 |
|
|
Universität Stuttgart |
2016 |
|
|
Universität Stuttgart |
2016 |
|
|
Universität Stuttgart |
2016 |
|
|
Universität Stuttgart |
2015 |
|
|
Universität Stuttgart |
2015 |
|
|
Universität Stuttgart |
2014 |
|
|
Universität Stuttgart |
2014 |
|
|
Universität Stuttgart |
2014 |
|
|
Universität Stuttgart |
2013 |
|
|
Universität Stuttgart |
2013 |
|
|
Universität Stuttgart |
2013 |
|
|
Universität Stuttgart |
2013 |
|
|
Universität Stuttgart |
2011 |
|
|
Universität Stuttgart |
2011 |
|
|
Universität Stuttgart |
2010 |
|
|
Universität Stuttgart |
2010 |
|
|
Universität Stuttgart |
2010 |
|
|
Universität Stuttgart |
2009 |
|
|
Universität Stuttgart |
2009 |
|
|
Universität Stuttgart |
2009 |
|
|
Universität Stuttgart |
2007 |
|
|
Universität Stuttgart |
2006 |
|
|
Universität Stuttgart |
2006 |
|
|
Universität Stuttgart |
2005 |
|
|
Universität Stuttgart |
2004 |
1 |
|
Universität Stuttgart |
2004 |
|
|
ETH Zürich |
2004 |
|
|
Universität Stuttgart |
2003 |
|
|
ETH Zürich |
2001 |
1 |
|
Universität Stuttgart |
1997 |
|
Development of new methods for system and control theory with main focus on:
- Nonlinear Control
- Networked Control
- Predictive Control
- Data-based Control
Application focuses:
- Process Control
- Mechatronics
- Biomedical Technology
- Nanotechnology
- Systems Biology
Universities
since 1999 Dean of Academic Affairs, Engineering Cybernetics, University of
Stuttgart
1999 – 2004 Deputy spokesperson, Collaborative Research Center SFB 412
2003 – 2012 Member, Review board Systems Engineering, DFG
2005 – 2013 Member, Governing Board Center for Systems Biology, University of
Stuttgart
since 2006 Liaison professor of the German Academic Scholarship Foundation
2006 – 2012 Member, Senate Structure Committee, University of Stuttgart
2006 – 2012 Member, “Ehrungskommission” (university-wide awards
committee), University of Stuttgart
seit 2007 Member of the Executive Board, Exzellence Cluster „Simulation
Technology” (2007-2018) and „Data-integrated Simulation Science“
(since 2019), University of Stuttgart
seit 2009 Chair, Graduate School „Simulation Technology”, University of
Stuttgart
seit 2009 Chair, Doctoral Grants Committee, Stuttgart Center for Simulation
Science
2009 – 2013 Member of the Management Board, Informatik Verbund Stuttgart
2012 – 2017 Member, Selection Committee for the Gottfried Wilhelm Leibniz
Programme, DFG
2012 – 2017 Chairman of the Jury, Communicator Award, Stifterverband and
DFG
2013 „Sounding Board“ Ingenieurwissenschaften@2025 of the Ministry
for Science and the Arts, Baden-Württemberg
2013 – 2016 Member of the Advisory Committee „Core data set science“
(Kerndatensatz), German Council of Science and Humanties
(Wissenschaftsrat)
2014 – 2018 Executive Director, Stuttgart Research Centre Systems Biology
2014 – 2015 Member of the Steering Group, Internationalen Research Training
Groups of the DFG
2014 – 2020 Chairman, des Gemeinsamen Ausschuss für Sicherheitsrelevante
Forschung von Leopoldina und DFG
2015 – 2020 Spokesperson, Research Alliance „System Mensch“ of the
Universities of Stuttgart and Tübingen
since 2017 Deputy Spokesperson, International Max Planck Research School
for Intelligent Systems , Stuttgart and Tübingen
2018 – 2020 Member, Expert Committee „Wissenschaft im digitalen Zeitalter“,
DFG
since 2018 Member, Cyber Valley Plenary Assembly
since 2019 Deputy Spokesperson, Excellence Cluster „Data-integrated
simulation science“
since 2019 Co-Director, Stuttgart Center for Simulation Science, University of
Stuttgart
since 2019 Member, Cyber Valley Research Fund Boards
2019 – 2020 Chairman, German National Research Data Infrastructure (NFDI)
Expert Committee
since 2020 Member, Interdisciplinary Commission for Pandemic Research,
DFG
since 2020 Founding Member, Interchange Forum for the Reflection of
Intelligent Systems
Scientific Organizations
2000 – 2015 Member of the Board, VDI/VDE-Gesellschaft Mess- und
Automatisierungstechnik (GMA)
2000 – 2015 Chairman, Fachbereich 1 „Grundlagen und Methoden der Mess-
und Automatisierungstechnik“ of the VDI/VDE-Gesellschaft Mess-
und Automatisierungstechnik (GMA)
2001 – 2008 Chairman, Technical Committee on Nonlinear Systems, International
Federation of Automatic Control (IFAC)
2001 – 2004 Council Member, European Union Control Association (EUCA)
2005 – 2008 Member, Policy Committee, Intern. Federation of Automatic
Control (IFAC)
2005 – 2008 Member, Board of Governors, IEEE Control Systems Society
2007 – 2012 Chairman, International Affairs Committee, IEEE Control Systems
Society
since 2008 Council Member, International Federation of Automatic Control
(IFAC)
2011 – 2014 Member, Board of Governors, IEEE Control Systems Society
2011 – 2015 Chairman, Strategic Planning Group, IFAC
2011 – 2016 Member, IEEE Life Sciences New Initiative (LSNI) Project Team
2012 – 2015 Member, Long Range Planning Committee, IEEE Control Systems
Society
2013 – 2014 Vice-president for Technical Activities, IEEE Control Systems
Society
2014 – 2017 Chairman, Administration & Finance Committee, IFAC
2014 – 2017 Member, IEEE Control Systems Award Committee
2014 – 2017 Chairman, Election Committee, IFAC
2017 – 2020 President, International Federation of Automatic Control (IFAC)
since 2017 Member, IFAC Publication Management Board
since 2020 Chairman, Membership Committee, IFAC
Editorial Activities
1997 – 2001 Associate Editor, Automatica (Elsevier)
1997 – 2008 Associate Editor, Journal of Process Control (Elsevier)
2001 – 2015 Editor, Automatica, Process and Computer Control Area (Elsevier)
2003 – 2007 Associate Editor, European Journal of Control (Hermes Science)
since 2008 Editor-in-Chief, Springer Lecture Notes in Control and Information
Sciences
2010 – 2016 Associate Editor, IMA Journal of Mathematical Control and
Information
since 1998 Member of various advisory boards for international journals
including IEE Proceedings on Control Theory and Applications
(since 2006 IET), Journal of Nonlinear and Robust Control,
Chemical Engineering Science, Canadian Journal of Chemical
Engineering, Control Handbook (CRC Press)