Adaptive and Learning-based Control

What it is about

You will learn principles and methods of adaptive and learning control, from online parameter estimation and adaptive observers to linear and nonlinear model reference methods. At the end you can design, dimension, and transfer adaptive controllers to applications, as well as apply basic machine learning approaches for system identification.

What you will be able to do

• Design adaptive control procedures
• Dimension adaptive controllers
• Apply online parameter estimation
• Deploy adaptive observers
• Assess linear system identification with ML methods
• Understand concurrent and iteratively learning controllers
• Apply gain-scheduling and robust adaptive control

What the module consists of

• VorlesungPresentation of the core ideas, classes of procedures and application areas of adaptive control
• ÜbungenDeepening of concepts through computational tasks, practical implementation of lecture procedures and development of extensions

Teaching method

• VorlesungIntroduction of theoretical foundations and typical applications
• Übungen mit HausaufgabenPractical solidification: Students work on tasks at home; solutions are presented and discussed in the exercise room
• MusterlösungenSupport for self-study and review of the exercises