Title: ADAPTIVE CONTROL
Catalog Description: Overview of basic approaches and alternatives to adaptive control; review of deterministic and stochastic signal and system models; real time parameter estimation using recursive least squares and its derivatives, persistent excitation; model reference adaptive systems, MIT rule, hyperstability approach; self-tuning regulators. Direct and Indirect methods, linear quadratic and generalized predictive control strategies, convergence analysis.
Coordinator: M. Kemal Cılız, Professor of Electrical Engineering
Goals: This course aims to introduce the basic concepts of parameter estimation and adaptive control of linear systems. It also covers the fundamentals of Lyapunov stability concepts related to adaptive control.
At the end of this course, students will be able to:
1. Understand how parameter estimation methods work for dynamic systems.
2. Understand the fundamental principles of model reference adaptive control.
3. Understand the basic principles of Lyapunov stability concepts related to adaptive control
4. Design simple adaptive controllers for linear systems using Lyapunov methods.
Text Book: K. J. Astrom and B. Wittenmark, Adaptive Control, 2nd Ed., Addison Wesley, 1995.
Reference Books: K.S. Narenda and A.M. Annaswamy, Stable Adaptive Systems, Prentice Hall, 1989.
S. Sastry and M. Bodson, Adaptive Control: Stability, Convergence and Robustness, Prentice Hall, 1989.
P. Ionnau and J. Sun, Robust Adaptive Control, Prentice Hall, 1996.
Prerequisites by Topic:
1. Linear algebra
2. Linear Systems theory
3. Real Analysis at introductory level
4. Ordinary differential equations
Topics to be Covered :
1. Introduction to Adaptive Control, concepts and approaches. What is adaptive control ?
2. Mathematical Preliminaries.
3. Deterministic Self Tuning Controllers.
4. Model Reference Adaptive Control.
5. Stability and robustness of adaptive controllers.
6. Applications and Practical Issues. Adaptive Robot Controllers.
Course Structure: The class meets for three lectures a week, each consisting of 50-minute sessions. There are one in-class mid-term exam and a final exam.
Final Exam %45
Term Project %30
(a) Apply math, science and engineering knowledge. This course covers the fundamentals of parameter estimation and adaptation techniques, Lyapunov stability using the basic linear systems background and real analysis techniques.
(c) Design a system, component or process to meet desired needs. The students are required to design simple adaptive controllers for linear systems.
(e) Ability to identify formulate and solve engineering problems. The course teaches the fundamentals to analyse and formulate the implementation of adaptive controllers.
(k) Use of modern engineering tools. Simulation exercises require the use of modern simulation tools.
Prepared By: M. Kemal Cılız