Optimal Control and Decision Making

Module Number: EI70140

Duration: 1 Semester

Reccurence: Winter Semester

Language: English

Number of ECTS: 5

Description of Achievement and Assessment Methods

A graded written exam that takes 90 minutes determines the grade of the module. It is verified that the students are able to transfer the methods they have learned in the lecture and deepened in the tutorials to similar problems in limited time.


Mathematics of dynamic systems and linear control theory from lectures of engineering mathematics and foundations of control.

Learning outcome

After taking the course students are able to analyse an optimal control problem and to formalize it as a static optimisation problem in the framework of model predictive control. The students are able to select an appropriate numerical method, to apply it, and even to develop it further.


Nonlinear programming: KKT conditions, QP method, SQP method, IP method; Dynamic optimisation: optimal control and dynamic programming; Linear model predictive control: constrained and unconstrained, Methods DMC, GPC; Nonlinear model predictive control; Stability of model predictive control; Numerics of model predictive control.

Teaching and learning methods

Lectures will be held ex cathedra. In exercises, repeated calculations and problem solving will help develop deeper understanding for the matter.


Types of media are as follows: - presentations - exercises and solutions


Papageorgiou, Leibold, Buss: Optimierung: Statische, Dynamische und Stochastische Verfahren für die Anwendung, Springer 2015. Camacho, Bordons, Model Predictive Control, Springer 2007. Grüne, Pannek, Nonlinear Model Predictive Control, Springer 2017.