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.

JEFFREY T. SPOONER is a senior member of the technical staff at Sandia National Laboratories, Albuquerque, New Mexico.

MANFREDI MAGGIORE is an assistant professor in the Department of Electrical and Computer Engineering at the University of Toronto, Canada.

RA?L ORD??EZ 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.

Introduction.

PART I: FOUNDATIONS.

Mathematical Foundations.

Neural Networks and Fuzzy Systems.

Optimization for Training Approximators.

Function Approximation.

PART II: STATE-FEEDBACK CONTROL.

Control of Nonlinear Systems.

Direct Adaptive Control.

Indirect Adaptive Control.

Implementations and Comparative Studies.

PART III:OUTPUT-FEEDBACK CONTROL.

Output-Feedback Control.

Adaptive Output Feedback Control.

Applications.

PART IV: EXTENSIONS.

Discrete-Time Systems.

Decentralized Systems.

Perspectives on Intelligent Adaptive Systems.

For Further Study.

Bibliography.

Index.