|Frau Prof. Dr. Melanie Zeilinger
Inst. Dynam. Syst. u. Regelungst.
ETH Zürich, LEE L 210
|+41 44 632 53 45
|Maschinenbau und Verfahrenstechnik
|Model Predictive Control
|2V + 1U
|Model predictive control is a flexible paradigm that defines the control law as an optimization problem, enabling the specification of time-domain objectives, high performance control of complex multivariable systems and the ability to explicitly enforce constraints on system behavior. This course provides an introduction to the theory and practice of MPC and covers advanced topics.
|Design and implement Model Predictive Controllers (MPC) for various system classes to provide high performance controllers with desired properties (stability, tracking, robustness,..) for constrained systems.
|- Review of required optimal control theory
- Basics on optimization
- Receding-horizon control (MPC) for constrained linear systems
- Theoretical properties of MPC: Constraint satisfaction and stability
- Computation: Explicit and online MPC
- Practical issues: Tracking and offset-free control of constrained systems, soft constraints
- Robust MPC: Robust constraint satisfaction
- Nonlinear MPC: Theory and computation
- Hybrid MPC: Modeling hybrid systems and logic, mixed-integer optimization
- Simulation-based project providing practical experience with MPC
|Script / lecture notes will be provided.
|Voraussetzungen / Besonderes
|One semester course on automatic control, Matlab, linear algebra.
Courses on signals and systems and system modeling are recommended. Important concepts to start the course: State-space modeling, basic concepts of stability, linear quadratic regulation / unconstrained optimal control.
Expected student activities: Participation in lectures, exercises and course project; homework (~2hrs/week).
|Risk Center Seminar Series
|A. Bommier, D. Basin, D. N. Bresch, L.‑E. Cederman, P. Cheridito, H. Gersbach, G. Sansavini, F. Schweitzer, D. Sornette, B. Stojadinovic, B. Sudret, U. A. Weidmann, S. Wiemer, M. Zeilinger, R. Zenklusen
|This course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling and governing complex socio-economic systems, and managing risks and crises. Students and other guests are welcome.
|Participants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop novel mathematical models and approaches for open problems, to analyze them with computers or other means, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to work scientifically on an internationally competitive level.
|This course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. For details of the program see the webpage of the seminar. Students and other guests are welcome.
|There is no script, but the sessions will be recorded and be made available. Transparencies of the presentations may be put on the course webpage.
|Literature will be provided by the speakers in their respective presentations.
|Voraussetzungen / Besonderes
|Participants should have relatively good scientific, in particular mathematical skills and some experience of how scientific work is performed.