Upon successfull completion of the course, the students will be able to:
a) design and analyze adaptive controllers for linear time invariant systems,
b) understand the problems, will analyze and design neuro-adaptive controllers for uncertain nonlinear systems in Brunovsky canonical form,
c) simulate and implement adaptive controllers using MATLAB.
Course Content (Syllabus)
1. Introduction (problem description, examples - applications).
2. Model Reference Adaptive Control (MRAC), (direct and Indirect control schemes, with-without normalization).
3. Adaptive Pole Placement Control (APPC), (polynomial approach, state-space approach, adaptive linear quadratic control).
4. Neuroadaptive Control of Uncertain Systems.
Additional bibliography for study
1.P.A. Ioannou, J. Sun, Robust Adaptive Control, Prentice Hall, New Jersey, 1996.
2.F.L. Lewis, S. Jagannathan, A. Yesildirek, Neural Network Control of Robot Manipulators and Nonlinear Systems, Taylor & Francis, London, 1999.
3.J.A. Farrell, M.M. Polycarpou, Adaptive Approximation Based Control, John Wiley & Sons, New Jersey, 2006.