After successful completion of the course, students are able to:

• characterize adaptive and model-predictive control methods
• model, derive and adapt model-predictive control problems in several variants (DMC, state-space-MPC)
• formulate and solve predictive control problems without and with constraints
• formulate relevant constraints of predictive control problems in an appropriate form
• find and interpret solutions of quadratic programming problems without and with constraints
• understand and apply stability measures for predictive control problems

• Basics of adaptive control
• Fundamentals of model predictive control
• Dynamic matrix control
• state space predictive control
• MPC with constraints
• stability of constrained MPC

The lecture is interactive. It is based on a structured, detailed lecture script, whereby numerous multimedia contents (illustrative videos, practical examples, MATLAB animations of relevant contexts and controller behavior) are also used to support the building of knowledge and understanding.

Students are interactively involved in scientific discussions and in close interaction with the exercise in terms of content.

Oral exam

Please register for the course via TISS in order to get access to the TUWEL course page.

English lecture notes can be purchased at the institute's secretariate (E325-04). It is also available at the first lecture unit.

A solid background in control theory (equivalent to courses 325.038 and 325.055) as well as basics of digital control (course 328.011) and multivariate state-space control (course 325.019) are recommended.