KON 442E - Introduction to Learning based Control Systems

Course Objectives

Understand the fundamental differences between classical and learning-based adaptive control methods.
Learn stability concepts such as Lyapunov stability and apply them in adaptive control design.
Develop skills to design model reference adaptive controllers for different system orders.
Gain knowledge about machine learning-based control methods, including neural networks.
Understand robust and advanced adaptive control methods and explore their real-world applications.

Course Description

Introduction, classical control and learning-based control, basic mathematical concepts, Lyapunov stability, MRAC design, adaptive dynamic inversion(ADI) control, Parameter convergence, MRAC design modifications for robustness, Parameter drift, Projection-based MRAC, machine learning-based approaches for MRAC, approximation-based adaptive control, MRAC for dynamic systems with unstructured and unmodeled dynamics, adaptive backstepping controller, concurrent and composite learning-based adaptive control, advanced control techniques using machine learning