This book provides the reader with a thorough grounding in the intelligent
control system design. Typical intelligent controller design is verified using
MATLAB simulation. In this book, concrete case studies, which present the results
of intelligent controller implementations, are used to illustrate the successful
application of the theory.
The book is structured as follows. The book starts with a brief introduction of
intelligent control in Chap. 1, expert control algorithm and design remarks are given
in Chap. 2, fuzzy sets and membersh ip function are introduced in Chap. 3 , fuzzy
logic controller design is introduced in Chap. 4 , fuzzy T-S modeling and control is
introduced in Chap. 5, adaptive fuzzy controller design and analysis are given in
Chap. 6, Neural network theory are introduced in Cha p. 7, in this Chapter, several
typical neural networks such as BP neural network and RBF neural network are
introduced, the basic design method of adaptive RBF neural network control and
adaptive sliding mode RBF neural network control are introduced in Chaps. 8 and 9,
respectively. Discrete RBF neural network controller design and analysis are given
in Chap. 10. Intelligent optimization algorithms are recommended in Chap. 11, and
at last, iterative learning control algorithm and applications are given in Chap. 12.
For each chapter, several engineering application examples are given. The contents
of each chapter in this book are independent, so that readers can their own needs.
In this book, all the control algorithms and their programs are described separately
and classified by the chapter name, which can be run successfully in MATLAB
7.5.0.342 version or in other more advanced versions. In addition, all the programs
can be downloaded via http://shi.buaa.edu.cn/liujinkun. If you have questions about
algorithms and simulation programs, please E-mail:ljk@buaa.edu.cn.
Beijing, China Jinkun Liu
