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.