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Model Predictive Control
Last Updated: 2026-02-05 16:08:42
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.
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
- Two A4 sheets of paper (4 pages, handwritten or computer typed)
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Model Predictive Control |
|
2 h weekly |
| exercise | Model Predictive Control |
|
1 h weekly |
Offered In
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed.)
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Robotics, Systems and Control (The courses listed in this category “Core Courses” are recommended. Alternative courses can be chosen in agreement with the tutor. .)
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed.)
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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.)
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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.)
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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.)
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Major Courses (A total of 42 CP must be achieved form courses during the Master Program. The individual study plan is subject to the tutor's approval.)
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Recommended Subjects (These courses are recommended, but you are free to choose courses from any other special field. Please consult your tutor.)
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Core Subjects (These core subjects are particularly recommended for the field of "Systems and Control".)
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Doctorate Information Technology and Electrical Engineering (More Information at: )
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Subject Specialisation (A minimum of 12 ECTS credit points must be obtained during doctoral studies (also see other categories for details) 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.)
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