Data-Driven Control

WS 2023/24

Lecturer: Dr.-Ing. Julian Berberich
Scope: 1.5L/0.5E
Credits: 3

General Information

Lecturer
Assistant
Prerequisites

"Einführung in die Regelungstechnik" (ERT) and "Konzepte der Regelungstechnik" (KRT) or equivalent lectures

Lectures

Wednesday 09:45-11:15 in room V9.41

First lecture: 18.10.2023

Content

Different control-theoretic approaches to analyzing systems and designing controllers based directly on measured data are covered. Among the topics that are handled are indirect data-driven control, the data informativity framework, and Willems' Fundamental Lemma.

Exam

The exam will be a written closed-book exam (i.e., keine Hilfsmittel!) and will last 60 minutes.

Literature

Indirect Data-Driven Control:

  • G. Pillonetto, F. Dinuzzo, T. Chen, G. De Nicolao, L. Ljung, "Kernel methods in system identification, machine learning and function estimation: A survey", Automatica, 2014, pp. 657-682.
  • 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 Conference, 2023, pp. 4155-4160.
  • M. Milanese, A. Vicino, "Optimal estimation theory for dynamic systems with set membership uncertainty: An overview", Automatica, 1991, pp. 997-1009.
  • C. Scherer, S. Weiland, "Linear matrix inequalities in control", Lecture Notes, Dutch Institute for Systems and Control, 2000.

Data informativity:

  • H. J. van Waarde, J. Eising, H. L. Trentelman, and M. K. Camlibel, "Data informativity: a new perspective on data-driven analysis and control", IEEE Transactions on Automatic Control, 2020, vol. 65, no. 11, pp. 4753-4768.
  • H. J. van Waarde, M. K. Camlibel, and M. Mesbahi, "From noisy data to feedback controllers: non-conservative design via a matrix S-lemma", IEEE Transactions on Automatic Control, 2022, vol. 67, no. 1, pp. 162-175.
  • A. Koch, J. Berberich, and F. Allgöwer, "Provably robust verification of dissipativity properties from data", IEEE Transactions on Automatic Control, 2022, vol. 67, no. 8, pp. 4248-4255.
  • J. Berberich, C. W. Scherer, F. Allgöwer, "Combining prior knowledge and data for robust controller design", IEEE Transactions on Automatic Control, 2022, doi: 10.1109/TAC.2022.3209342.

Willems' Fundamental Lemma:

  • J. C. Willems, P. Rapisarda, I. Markovsky, and B. De Moor, "A note on persistency of excitation", Systems & Control Letters, 2005, vol. 54, pp. 325-329.
  • I. Markovsky and P. Rapisarda, "Data-driven simulation and control", International Journal of Control, 2008, vol. 81, no. 12, pp. 1946-1959.
  • J. Coulson, J. Lygeros, and F. Dörfler, "Data-enabled predictive control: In the shallows of the DeePC", in Proc. European Control Conference, 2019, pp. 307-312.
  • J. Berberich, J. Köhler, M. A. Müller, and F. Allgöwer, "Data-driven model predictive control with stability and robustness guarantees", IEEE Transactions on Automatic Control, 2021, vol. 66, no. 4, pp. 1702-1717.
  • A. Romer, J. Berberich, J. Köhler, and F. Allgöwer, "One-shot verification of dissipativity properties from input-output data", IEEE Control Systems Letters, 2019, vol. 3, no. 3, pp. 709-714.
  • 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 Conference, 2023, pp. 4155-4160.
This image shows Julian Berberich

Julian Berberich

Dr.-Ing.

Lecturer (Akademischer Rat)

This image shows Robin Strässer

Robin Strässer

M.Sc.

Research Assistant

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