Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis, and MATLAB Simulation
Jinkun Liu, Beijing University of Aeronautics and Astronautics
Springer International Publishing, 2013
ISBN: 978-3-642-34816-7;
Language: English
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 objective of the text is 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, and motors. 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 researchers in the fields of neural adaptive control, mechanical systems, MATLAB simulation, engineering design, robotics, and automation.
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