Johannes Köhler: Katalogdaten im Herbstsemester 2021 |
| Name | Herr Dr. Johannes Köhler |
| Adresse | Intelligente Regelsysteme ETH Zürich, LEE L 208 Leonhardstrasse 21 8092 Zürich SWITZERLAND |
| jkoehle@ethz.ch | |
| Departement | Maschinenbau und Verfahrenstechnik |
| Beziehung | Dozent |
| Nummer | Titel | ECTS | Umfang | Dozierende | |
|---|---|---|---|---|---|
| 151-0371-00L | Advanced Model Predictive Control  Number of participants limited to 60. | 4 KP | 2V + 1U | M. Zeilinger, A. Carron, L. Hewing, J. Köhler | |
| Kurzbeschreibung | Model predictive control (MPC) has established itself as a powerful control technique for complex systems under state and input constraints. This course discusses the theory and application of recent advanced MPC concepts, focusing on system uncertainties and safety, as well as data-driven formulations and learning-based control. | ||||
| Lernziel | Design, implement and analyze advanced MPC formulations for robust and stochastic uncertainty descriptions, in particular with data-driven formulations. | ||||
| Inhalt | Topics include - Review of Bayesian statistics, stochastic systems and Stochastic Optimal Control - Nominal MPC for uncertain systems (nominal robustness) - Robust MPC - Stochastic MPC - Set-membership Identification and robust data-driven MPC - Bayesian regression and stochastic data-driven MPC - MPC as safety filter for reinforcement learning | ||||
| Skript | Lecture notes will be provided. | ||||
| Voraussetzungen / Besonderes | Basic courses in control, advanced course in optimal control, basic MPC course (e.g. 151-0660-00L Model Predictive Control) strongly recommended. Background in linear algebra and stochastic systems recommended. | ||||