MAE 282 - Adaptive Control (Fall 2006)

Department of AMES, UCSD

Course web address: http://mae.ucsd.edu/research/krstic/krstic/teaching/282/282.html

Instructor: Prof. Miroslav Krstic, 1808 EBUI, 822-1374, krstic@ucsd.edu

TEXTs:

• Krstic, Kanellakopoulos, and Kokotovic, Nonlinear and Adaptive Control Design, Wiley, 1995.
• Ariyur and Krstic, Real-Time Optimization by Extremum Seeking Control, Springer, 2003.

Supplemental Reading: Ioannou and Sun, Robust Adaptive Control, Prentice Hall, 1996.

Prerequisites: MAE 281A or consent of instructor

Time and Place: Wednesday 5-8pm, room TBA

 

Office Hours:

Stop by any time.

Grading: (click on highlighted items for problem sets)

Homework 40%
Final 60%

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.