Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques
- Includes a solution manual for problems.
- Provides MATLAB code for examples and solutions.
- Deals with robust systems in both theory and practice.
PART I: FOUNDATIONS.
Neural Networks and Fuzzy Systems.
Optimization for Training Approximators.
PART II: STATE-FEEDBACK CONTROL.
Control of Nonlinear Systems.
Direct Adaptive Control.
Indirect Adaptive Control.
Implementations and Comparative Studies.
PART III:OUTPUT-FEEDBACK CONTROL.
Adaptive Output Feedback Control.
PART IV: EXTENSIONS.
Perspectives on Intelligent Adaptive Systems.
For Further Study.
MANFREDI MAGGIORE is an assistant professor in the Department of Electrical and Computer Engineering at the University of Toronto, Canada.
RAÚL ORDÓÑEZ is an assistant professor in the Department of Electrical and Computer Engineering at the University of Dayton, Ohio.
KEVIN M. PASSINO is a professor in the Department of Electrical Engineering at The Ohio State University.
“…the text is well organised with topics judiciously selected to build on each other…the discussion and motivations are rigorous…” (International Journal of Robust & Nonlinear Control, Vol.15, No.1, 10th January 2005)
"...this is an excellent book. It is pedagogically sound and, hence, suitable as a text for graduate courses.... I recommend it also as a very valuable resource to practitioners..." (International Journal of General Systems, Vol. 32, 2003)