Intelligent Control Systems

Theory and application of intelligent control systems, i.e., the combination of machine learning and control theory.

Topics:

• Introduction to Nonlinear Control and ICS

• Learning nonlinear dynamical systems

• Sum of Basis functions

• Artificial neural networks, deep learning, and other advanced neural architectures in the context of ICS

• Symbolic regression

• Gaussian processes

• Reinforcement learning

• Imitation learning

• Adaptive control

• Iterative learning control

We will strive for a balance between practical intuition and theoretical understanding, discussing examples of applications and delving deeper into the theory when feasible.

The examination will be as follows:

(i) practical assignment and (ii) written exam, open book.

You must score at least 6 on both assignments to get a pass.

Under the master's program regulations:

• Students will have the opportunity to retake the written examination if they fail.

• If your practical assignment is graded between 5 and 5.75, you will have two weeks to integrate the assessor's feedback. If this is done satisfactorily, you can be rewarded with a mark that is not higher than 6/10. The exact instructions for the addition will be announced after the grading of the PA is concluded.