151-0371-00L Advanced Model Predictive Control
Semester | Autumn Semester 2022 |
Lecturers | M. Zeilinger, A. Carron, L. Hewing, J. Köhler |
Periodicity | yearly recurring course |
Language of instruction | English |
Comment | Number of participants limited to 60. |
Courses
Number | Title | Hours | Lecturers | ||||
---|---|---|---|---|---|---|---|
151-0371-00 V | Advanced Model Predictive Control | 2 hrs |
| M. Zeilinger, A. Carron, L. Hewing, J. Köhler | |||
151-0371-00 U | Advanced Model Predictive Control | 1 hrs |
| M. Zeilinger, A. Carron, L. Hewing, J. Köhler |
Catalogue data
Abstract | 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. |
Objective | Design, implement and analyze advanced MPC formulations for robust and stochastic uncertainty descriptions, in particular with data-driven formulations. |
Content | Topics include - Nominal MPC for uncertain systems (nominal robustness) - Robust MPC - Stochastic MPC - Review of regression methods - Set-membership Identification and robust data-driven MPC - Bayesian regression and stochastic data-driven MPC - MPC as safety filter for reinforcement learning |
Lecture notes | Lecture notes will be provided. |
Prerequisites / Notice | 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. |
Performance assessment
Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
ECTS credits | 4 credits |
Examiners | M. Zeilinger, A. Carron, L. Hewing, J. Köhler |
Type | session examination |
Language of examination | English |
Repetition | The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit. |
Mode of examination | oral 20 minutes |
Additional information on mode of examination | The final grade is based on an exam and an optional take-home project. The exam takes place during the examination session. The project is a continuous performance assessment (learning task) and requires the student to understand and apply the lecture material. The grade of the project may contribute 0.25 grade points to the final grade, but only if it helps improving the final grade. |
This information can be updated until the beginning of the semester; information on the examination timetable is binding. |
Learning materials
No public learning materials available. | |
Only public learning materials are listed. |
Groups
No information on groups available. |
Restrictions
There are no additional restrictions for the registration. |