Course web address: http://mae.ucsd.edu/research/krstic/krstic/teaching/282/282.html
Supplemental Reading: Ioannou and Sun, Robust Adaptive Control, Prentice Hall, 1996.
Prerequisites: MAE 281A or consent of instructor
Time and Place: TuTh 8-9:20 am, WLH 2113
Final Exam: Th June 10, 8-11 am, WLH 2113
Office Hours: Stop by any time.
Grading: (click on highlighted items for problem sets)
Course Objective: While methods of robust control, developed based on a priori bounds of system uncertainty, are applicable to systems with smaller levels of uncertainty, methods of adaptive control can potentially handle larger uncertainties by "learning" them on-line. This course will introduce graduate students into the state-of-the-art design methods of adaptive control, and their limitations.
Topics:Parametric models. Parameter identifiers and algorithms: SPR-Lyapunov, gradient, least-squares. Persistence of excitation. Adaptive observers. Certainty equivalence principle. Model reference adaptive control. Indirect adaptive control: pole placement, polynomial approach, LQR. Robustification: parameter drift, leakage, projection, dead-zone, dynamic normalization. Adaptive nonlinear control: tuning functions and modular design. Extremum seeking.