Strategies for Feedback Linearisation: A Dynamic Neural Network Approach / Edition 1

Strategies for Feedback Linearisation: A Dynamic Neural Network Approach / Edition 1

by Freddy Rafael Garces, Victor Manuel Becerra, Chandrasekhar Kambhampati, Kevin Warwick
     
 

ISBN-10: 1852335017

ISBN-13: 9781852335014

Pub. Date: 05/07/2003

Publisher: Springer London

Using relevant mathematical proofs and case studies illustrating design and application issues, this book demonstrates this powerful technique in the light of research on neural networks, which allow the identification of nonlinear models without the complicated and costly development of models based on physical laws.  See more details below

Overview

Using relevant mathematical proofs and case studies illustrating design and application issues, this book demonstrates this powerful technique in the light of research on neural networks, which allow the identification of nonlinear models without the complicated and costly development of models based on physical laws.

Product Details

ISBN-13:
9781852335014
Publisher:
Springer London
Publication date:
05/07/2003
Series:
Advances in Industrial Control Series
Edition description:
2003
Pages:
171
Product dimensions:
0.50(w) x 9.21(h) x 6.14(d)

Table of Contents

1. Introduction.- 2. Fundamental Concepts.- 3. Introduction to Feedback Linearisation.- 4. Dynamic Neural Networks.- 5. Nonlinear System Approximation Using Dynamic Neural Networks.- 6. Feedback Linearisation Using Dynamic Neural Networks.- 7. Case Studies.- References.

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