What it is about
You learn methods of optimal control, optimization, model predictive control and learning-based controller design (including reinforcement learning). In the end you can formulate problems of optimal control, select numerical solution procedures and implement controllers as well as evaluate modern learning-based approaches.
What you will be able to do
- Analysis and formalization of a problem of optimal control
- Derivation of optimal controllers for various applications
- Selection of an appropriate numerical algorithm
- Implementation of an optimal controller and analysis of its properties
- Understanding and design of learning-based controller designs and reinforcement learning
What the module consists of
- VorlesungenIntroduction to the fundamental concepts
- ÜbungsbetriebWorking on examples to deepen understanding
- AufgabenTransferring the concepts to practical problems
Teaching method
- VorlesungenIntroduction to the fundamental concepts
- ÜbungsbetriebApplication and practice using examples
- AufgabenTransfer of concepts to practical problems