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

Advanced Model Predictive Control

Lecturers: Prof. Dr. Melanie Zeilinger

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

Does not take place this semester. Number of participants limited to 60.

VVZ CR n/a

Last Updated: 2026-06-03 00:07:38

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 Does not take place this semester. The course will not be offered in the Autumn Semester 2026 and will instead take place in the Spring Semester 2027.	No time listed	2 h weekly
exercise	Advanced Model Predictive Control Does not take place this semester. The course will not be offered in the Autumn Semester 2026 and will instead take place in the Spring Semester 2027.	No time listed	1 h weekly

Offered In

Mechanical Engineering Master
- Core Courses (The Core Courses in the Master’s program Mechanical Engineering listed below are indicative and include courses designed by the Department at the Master's level. With the approval of the tutor, students may also select Master's-level courses offered by other departments at ETH. These courses will be marked as non-regular in the LAG, but their categorization as Core Courses is possible if included in the approved LAG.)
Computational Science and Engineering Master
- Fields of Specialization
  - Systems and Control
Electrical Engineering and Information Technology Master
- 01 - Courses of specializations
  - Tracks (all): Electives (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.)
  - Track: 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.)
    - Specialisation Courses (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
- Core Courses
Doctorate Information Technology and Electrical Engineering (A minimum of 12 ECTS credit points must be obtained during doctoral studies (also see sub-categories for details) More Information at )
- Subject Specialisation (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
- Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
  - Robotics
    - Deep Track Robotics (These courses can be credited either as a specialization subject or as an elective subject.)