Optimization for Control Engineering ()
|Position within curricula||See TUMonline|
After taking the course students are able to analyse a technical problem and to formalize it as a mathematical optimization problem. The students are able to select an appropriate numerical method, to apply it, and even to develop it further. As basis for the numerical application, students understand the most important results from the mathematical theory. Also they are able to solve simple problems of optimization analytically.
Introduction - Static Optimization: Minimization of scalar and vector functions with/without equality and/or inequality constraints; gradient- and non-gradient-based methods; least-squares; convex optimization; linear programming; numerical algorithms. - Dynamic Optimization: Variational calculus; minimum-principle; dynamic programming; numerical methods. - Applications: control and filter design
Fundamentals of control engineering and advanced knowledge in mathematics.
written test 90 min
Lecture work sheets and M. Papageorgiou, M. Leibold, M. Buss, "Optimierung". Springer Vieweg, 4. Auflage, 2015.