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Nonlinear Identification and Control
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Nonlinear Identification and Control

Nonlinear Identification and Control

A Neural Network Approach

G. P. Liu

210 pages, parution le 21/01/2002

Résumé

The purpose of this monograph is to give the broad aspects of nonlinear identification and control using neural networks. It consists of three parts:
  • an introduction to the fundamental principles of neural networks;
  • several methods for nonlinear identification using neural networks;
  • various techniques for nonlinear control using neural networks.
A number of simulated and industrial examples are used throughout the monograph to demonstrate the operation of nonlinear identification and control techniques using neural networks. It should be emphasised that the methods and systems of nonlinear control have not progressed as rapidly as those for linear control. Comparatively speaking, at the present time, they are still in the development stage. We believe that the fundamental theory, various design methods and techniques, and several applications of nonlinear identification and control using neural networks that are presented in this monograph will enable the reader to analyse and synthesise nonlinear control systems quantitatively.

Contents

  • Neural Networks.
  • Sequential Nonlinear Identification.
  • Recursive Nonlinear Identification.
  • Multi
  • objective Nonlinear Identification.
  • Wavelet
  • Based Nonlinear Identification.
  • Nonlinear Adaptive Neural Control.
  • Nonlinear Predictive Neural Control.
  • Variable Structure Neural Control.
  • Neural Control Application to Combustion Processes.

Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) G. P. Liu
Parution 21/01/2002
Nb. de pages 210
Format 16 x 24
Couverture Relié
Poids 450g
Intérieur Noir et Blanc
EAN13 9781852333423
ISBN13 978-1-85233-342-3

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