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151-0660-00L 4 Credits BSC , DR , MSC D-ERDW , D-ARCH , D-INFK , D-MATH , D-MAVT , D-PHYS , D-ITET

Model Predictive Control

Lecturers & Examiners: Prof. Dr. Melanie Zeilinger

VVZ CR 3.4

Last Updated: 2026-06-03 00:14:14

Abstract

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.

Objective

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.

Content

- 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 - Simulation-based project providing practical experience with MPC

Resources

Lecture Notes

Script / lecture notes will be provided.

Learning Materials (Links)

Main link
Course webpage

General Information

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

Examination

Type: session examination
Mode: written 120 minutes
Aids: Four A4 pages (2 A4 sheets double-sided or 4 A4 sheets single-sided, handwritten or computer typed)

Course Components

Type	Title	Time & Place	Hours
lecture	Model Predictive Control	Thu 10:15-12:00 (ML D 28)	2 h weekly
exercise	Model Predictive Control	Thu 12:15-13:00 (ML D 28)	1 h weekly

Offered In

Mechanical Engineering Bachelor
- Bachelor Studies (Programme Regulations 2022)
  - Focus Specialization
    - Robotics, Systems and Control (Focus Coordinator: Prof. Robert Katzschmann)
Computational Science and Engineering Bachelor
- Additional Electives from the Fields of Specialization (CSE Master) (recognition of 227-0662-00L and 227-0662-10L requires the successful completion of both course units)
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
Mathematics Master
- Application Area (Only necessary and eligible for the Master degree in Applied Mathematics. One of the application areas specified must be selected for the category Application Area for the Master degree in Applied Mathematics. At least 8 credits are required in the chosen application area. Credits from other application areas cannot be recognised for further application areas.)
  - Control and Automation
Electrical Engineering and Information Technology Master
- 01 - Courses of specializations
  - Track: Systems and Control (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Systems and Control", see . The individual study plan is subject to the tutor's approval.)
    - Core Courses (These core courses are particularly recommended for the field of "Systems and Control". You may choose core courses form other fields in agreement with your tutor. A minimum of 24 credits must be obtained from core courses during the MSc EEIT.)
      - Advanced Core Courses
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 but a small selection out of a much larger available number of courses. Please discuss your course selection with your PhD supervisor.)
Integrated Building Systems Master
- Main Courses
  - Specialised Courses
Data Science Master
- Master Studies (Programme Regulations 2023)
  - Electives
    - Interdisciplinary Electives
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.)