Stochastic Control

 

The module provides an introduction to stochastic processes and stochastic control. It mainly focuses on Bayesian filtering theory and on stochastic differential equations.

Topics covered in the module are

• Basic facts about stochastic processes,
• Bayesian estimation and filtering theory,
• Introduction to stochastic differential equations, and Ito calculus as well as
• Applications in control and optimization.

Recommended prerequisites are basic knowledge about linear systems and control (e.g. System Theory I and II).

More detailed information on the course may be found on RWTHonline.

The teaching material is available on RWTHmoodle.