Title: Nonlinear Model Predictive Control - Theory and Applications

Lecturer: Dr. Timm Faulwasser

Assistants: Tillmann Mühlpfordt (Campus Nord, G449 R256), Alexander Engelmann (Campus Nord, G449, R256)

Credits: 5 ECTS

During the Summer term (Sommersemester) we will offer a course on

 Nonlinear Model Predictive Control - Theory and Applications


Model Predictive Control (MPC) “[…] is the only advanced control technique—that is, more advanced than standard PID control—to have had a significant and widespread impact on industrial process control” (Jan Maciejowski, Predictive control: with constraints Pearson Education Limited, 2002).

The course will cover the following topics:

  • Optimality conditions for static optimization problems
  • Basics of Optimal Control Theory, Pontryagin Maximum Principle
  • Formulation of Optimal Control Problems
  • Primer on numerical solution methods (shooting methods and collocation)
  • Principle of nonlinear model predictive control
  • Sufficient stability conditions with and without terminal constraints
  • Implementation aspects of NMPC
  • Research outlook: NMPC for energy systems, path following for robots, ...


The course is worth 4 ECTS credits. It will be held on the following dates:

  • Start: 24.04.2017 09:45--11:15, 11:30--13:00 (Campus Süd, G50.34 R107)
  • End: 24.07.2017 09:45--11:15,  (Campus Süd G50.34 R107)

Required software:

  • Matlab >=  Version 2013a
  • Optimization toolbox (fmincon, quadprog, linprog, ...)
  • Yalmip
  • CasADi
  • Optistack

The course will involve pen&paper exercsises as well as in-class computer exercises (Matlab), for which students should bring their laptops. Furthermore, there will be take-home projects, which contribute to the final grade. The guidelines are

  • project report of 10 to 20 pages
  • concise project presentation
  • project involves problem formulation and problem solution.
  • Lecturer and teaching assistants are available at any time.
  • deadlines to be announced

The course is part of the Vertiefungsfach "Robotik und Automation" of the Master Computer Science.

Slides and problem sets can be downloaded from Ilias.

For further information click here


  • Maciejowski, J. Predictive control: with constraints Pearson Education Limited, 2002
  • Rawlings, J. & Mayne, D. Model Predictive Control: Theory & Design Nob Hill Publishing, Madison, WI, 2009
  • Mayne, D.; Rawlings, J.; Rao, C. & Scokaert, P. Constrained model predictive control: Stability and optimality Automatica, 2000, 36, 789-814
  • Further references: see last slides of introductory lecture.