Radial Basis Function (RBF) Neural Network Control
for Mechanical Systems is motivated by the need for systematic
design approaches to stable adaptive control system design using neural
network approximation-based techniques. The main objectives of the book
are to introduce the concrete design methods and MATLAB simulation of
stable adaptive RBF neural control strategies. In this book, a broad
range of implementable neural network control design methods for
mechanical systems are presented, such as robot manipulators, inverted
pendulums, single link flexible joint robots, motors, etc. Advanced
neural network controller design methods and their stability analysis
are explored. The book provides readers with the fundamentals of neural
network control system design.
This book is intended for the researchers in the fields of neural
adaptive control, mechanical systems, Matlab simulation, engineering
design, robotics and automation.
Jinkun Liu is a professor at Beijing University of Aeronautics and
Astronautics.