This image shows Lukas Schwenkel

Lukas Schwenkel

M.Sc.

Research Assistant
Institute for Systems Theory and Automatic Control

Contact

+49 711 685 67744
+49 711 685 67735

Pfaffenwaldring 9
70569 Stuttgart
Germany
Room: 3.234

Office Hours

On appointment

Subject

I'm working in the field of Model Predictive Control (MPC). My research focuses on robust MPC for uncertain systems that are affected by disturbances.

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. L. Schwenkel, M. Gharbi, S. Trimpe, and C. Ebenbauer, “Online learning with stability guarantees: A memory-based warm-starting for real-time MPC,” Automatica, vol. 122, p. 109247, 2020, doi: 10.1016/j.automatica.2020.109247.
  7. 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.
  8. 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). Jeju, South Korea, 2020, pp. 1235–1241. doi: 10.1109/CDC42340.2020.9303819.
  9. L. Schwenkel, M. Guo, and M. Bürger, “Optimizing Sequences of Probabilistic Manipulation Skills Learned from Demonstration,” in Proceedings of the Conference on Robot Learning, in Proceedings of the Conference on Robot Learning, vol. 100. PMLR, 2020, pp. 273--282. [Online]. Available: http://proceedings.mlr.press/v100/schwenkel20a.html
  10. L. Schwenkel, M. Gharbi, S. Trimpe, and C. Ebenbauer, “Online learning with stability guarantees: A memory-based real-time model predictive controller,” arXiv:1812.09582, 2018. [Online]. Available: https://arxiv.org/abs/1812.09582

since 07/2019

Research Assistant at the Institute for Systems Theory and Automatic Control, University of Stuttgart

04/2017 −  05/2019

Master studies Engineering Cybernetics at the University of Stuttgart

Master thesis: "Leveraging Data in Model Predictive Control"

12/2018 − 05/2019

Internship at Bosch Center for Artificial Intelligence (BCAI), Robert Bosch GmbH, Renningen

Topic: Learning from Demonstration

10/2014 − 03/2017

Bachelor studies Engineering Cybernetics at the University of Stuttgart

Bachelor thesis: "Accelerated Gradient Methods for Convex Optimization"

10/2012 − 09/2014

Studies Mathematics and Physics for teaching at the University of Tübingen, without graduation due to change of subject.

06/2012

Abitur at the Graf Eberhard Gynmasium in Bad Urach

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