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Last Updated: 2026-02-05 14:55:28
Abstract
System complexity and demanding performance render traditional control inadequate. Applications from the process industry to the communications sector increasingly use MPC. The last years saw tremendous progress in this interdisciplinary area. The course first gives an overview of basic concepts and then uses them to derive MPC algorithms. There are exercises and invited speakers from industry.
Objective
Introduction to the theory and application of Model Predictive Control (MPC).
Content
In its present form MPC was first proposed by industry to deal with the control of multivariable systems with a potentially large number of inputs and outputs subject to constraints. The constraints can arise from limits on the manipulated variables or from specifications on some outputs which should not be exceeded. In the last few years a theoretical basis for MPC has emerged which provides strong stability and robustness guarantees (i.e. stability and performance in the presence of model uncertainty) for both linear and nonlinear systems. The course will be based on the draft version of a book by Morari, Garcia, Lee and Prett and will make use of the new Model Predictive Control Toolbox for Matlab which is distributed by the MathWorks.
General Information
- Language
- German
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Model Predictive Control
Wird als Blockkurs durchgeführt.
|
No time listed | 4 h weekly |