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151-0371-00L 4 Credits DR , MSC D-ITET , D-MAVT , D-ERDW , D-INFK , D-MATH , D-PHYS

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Advanced Model Predictive Control

Lecturers & Examiners: Prof. Dr. Melanie Zeilinger, Dr. Andrea Carron, Dr. Johannes Köhler

Number of participants limited to 60.

VVZ CR n/a

Last Updated: 2026-06-01 11:30:56

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

Resources

Lecture Notes

Lecture notes will be provided.

General Information

Language: English
Levels: DR , MSC
Frequency: Yearly recurring

Examination

Type: session examination
Mode: oral 20 minutes

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.

Course Components

Type	Title	Time & Place	Hours
lecture	Advanced Model Predictive Control	Thu 10:15-12:00 (ML F 39)	2 h weekly
exercise	Advanced Model Predictive Control	Thu 12:15-13:00 (ML F 39)	1 h weekly

Offered In

Maschineningenieurwissenschaften Master
- Kernfächer
Rechnergestützte Wissenschaften Master
- Vertiefungsgebiete
  - Systems and Control
Elektrotechnik und Informationstechnologie Master
- 01 - Fächer der Vertiefungen
  - Vertiefungen (alle): Wahlfächer (This is only a short selection. Other courses from the ETH course catalogue may be chosen in agreement with your tutor. As an alternative to the elective courses, students may do a second semester project or an internship in industry. Please consult your tutor.)
  - Vertiefung: Systems and Control (The core courses and specialisation courses below are a selection for students who wish to specialise in the area of "Systems and Control", see . The individual study plan is subject to the tutor's approval.)
    - Vertiefungsfächer (These specialisation courses are particularly recommended for the area of "Systems and Control", but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialisation courses during the Master's Programme.)
Robotics, Systems and Control Master
- Kernfächer
Doktorat Informationstechnologie und Elektrotechnik (A minimum of 12 ECTS credit points must be obtained during doctoral studies (also see sub-categories for details) More Information at )
- Vertiefung Fachwissen (The courses on offer below are only a small selection out of a much larger available number of courses. Please discuss your course selection with your PhD supervisor.)
Space Systems Master
- Fachspezifische Vertiefung (Es müssen mindestens 20 KP aus den Deep Track Lerneinheiten absolviert werden. Überzählige KP können für Wahlfächer angerechnet werden.)
  - Robotics
    - Vertiefungsfächer Robotics (Diese LE's können sowohl als Vertiefungsfach als auch als Wahlfach angerechnet werden.)