Introduction to the theory and methodology used to design adaptive controllers for uncertain systems, addressing issues such as input constraints, disturbance rejection, partial measurements, and robustness.
Why take this course?
This course provides a mathematically rigorous introduction to the field of adaptive control. Concepts are presented in the context of nonlinear time-varying and time-invariant systems. The concepts taught in this course are considered advanced in the field of modern control theory, and can also be used in the fields of system identification and signal processing.
ECE 5774 and ECE 5744 or ME 5544 and ME 5574 or AOE 5774 and AOE 5744.
Major Measurable Learning Objectives
Assess the stability of autonomous and nonautonomus systems.
Design a model reference adaptive control system for a given system considering matched structured nonlinearities or uniformly bounded residual nonlinearities.
Address real-life problems during the design of a model-reference adaptive controller such as input constraints, disturbance rejection, partial measurements, and robustness.
Percentage of Course
1. Review of Lyapunov analysis
2. model Reference Adaptive Control
3. Composite Adaptation
4. Parameter Convergence: Persistency of Excitation or Uniform Complete Observability
5. Adaptive Control in the Presence of Input Constraints
6. Direct MRAC for Nonlinear systems with Matched Structured Nonlinearities
7. Robustness of MRAC: Parameter Drift
8. Adaptive Control in the Presence of Uniformly Bounded Residual Nonlinearity