|
- Discussion of the key characteristics of nonlinear static and dynamic
optimization problems
- Analytical and numerical solution methods for static and dynamic
optimization problems
- Derivation of optimal control strategies for nonlinear systems
- Dynamic Programming, principle of optimality,
Hamilton-Jacobi-Bellman-equation
- Variational calculus
- Pontryagin Maximum Principle
- Numerical algorithms for the solution of optimal control problems
- Infinite and finite horizon optimal control
- LQ optimal control
- Application examples from various fields such as mechanical
engineering, robotics and aeronautics
- Introduction to nonlinear model predictive control
- Introduction to game theory
The exercises partly consist of project work in which the students
apply their knowledge to solve particular optimal control problems
for application case studies.
|
JD) | © Universität Stuttgart |
Impressum