Systems and Control covers modeling, analysis, and control of dynamical systems. It acquaints students with the basics of dynamical system theory and also equips them with the tools necessary for control system design. It emphasizes design and demonstrates how dynamical system theory fits into practical applications. Classical methods and the techniques of post-modern control engineering are presented in a unified fashion, showing how the current tools of a control engineer supplement more classical tools.

Broad in scope, Systems and Control shows the multidisciplinary role of dynamics and control. It presents neural networks, fuzzy systems, and genetic algorithms and provides a self-contained introduction to chaotic systems. The text employs Lyapunov's stability theory as a unifying medium for different types of dynamical systems, using it--with its variants--to analyze dynamical system models. Specifically, optimal, fuzzy, sliding mode, and chaotic controllers are all constructed with the aid of the Lyapunov method and its extensions. In addition, a class of neural networks is also analyzed using Lyapunov's method.

Ideal for advanced undergraduate and beginning graduate courses in systems and control, this text can also be used for introductory courses in non-linear systems and modern automatic control. It requires previous knowledge of basic differential equations and elements of linear algebra and provides a review of the necessary mathematical techniques and terminology

CONTENTS

Each chapter ends with Notes and Exercises
1. Dynamical Systems and Modeling
2. Analysis of Modeling Equations
3. Linear Systems
4. Stability
5. Optimal Control
6. Sliding Modes
7. Vector Field Methods
8. Fuzzy Systems
9. Neural Networks
10. Genetic and Evolutionary Algorithms
11. Chaotic Systems and Fractals
Appendix: Math Review
Notes
Exercises
Bibliography
Index