Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation

Author:   Jinkun Liu
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2013 ed.
ISBN:  

9783642434556


Pages:   365
Publication Date:   26 June 2015
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Our Price $448.77 Quantity:  
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation


Overview

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.

Full Product Details

Author:   Jinkun Liu
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2013 ed.
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   5.796kg
ISBN:  

9783642434556


ISBN 10:   364243455
Pages:   365
Publication Date:   26 June 2015
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- RBF Neural Network Design and Simulation.- RBF Neural Network Control Based on Gradient Descent Algorithm.- Adaptive RBF Neural Network Control.- Neural Network Sliding Mode Control.- Adaptive RBF Control Based on Global Approximation.- Adaptive Robust RBF Control Based on Local Approximation.- Backstepping Control with RBF.- Digital RBF Neural Network Control.- Discrete Neural Network Control.- Adaptive RBF Observer Design and Sliding Mode Control.

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