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Nonlinear Identification and Control A Neural Network Approach

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer met...

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Bibliographic Details
Main Author: Liu, G.P.
Format: eBook
Language:English
Published: London Springer London 2001, 2001
Edition:1st ed. 2001
Series:Advances in Industrial Control
Subjects:
Dynamical Systems
Applied Dynamical Systems
Artificial Intelligence
Control And Systems Theory
Nonlinear Theories
Control Engineering
Dynamics
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 8.4 Generalised Variable Structure Neural Control
  • 8.5 Recursive Learning for Variable Structure Control
  • 8.6 An Example
  • 8.7 Summary
  • 9. Neural Control Application to Combustion Processes
  • 9.1 Introduction
  • 9.2 Model of Combustion Dynamics
  • 9.3 Neural Network Based Mode Observer
  • 9.4 Output Predictor and Controller
  • 9.5 Active Control of a Simulated Combustor
  • 9.6 Active Control of an Experimental Combustor
  • 9.7 Summary
  • 4.4 Multiobjective Identification Algorithm
  • 4.5 Examples
  • 4.6 Summary
  • 5. Wavelet Based Nonlinear Identification
  • 5.1 Introduction
  • 5.2 Wavelet Networks
  • 5.3 Identification Using Fixed Wavelet Networks
  • 5.4 Identification Using Variable Wavelet Networks
  • 5.5 Identification Using B-spline Wavelets
  • 5.6 An Example
  • 5.7 Summary
  • 6. Nonlinear Adaptive Neural Control
  • 6.1 Introduction
  • 6.2 Adaptive Control
  • 6.3 Adaptive Neural Control
  • 6.4 Adaptation Algorithm with Variable Networks
  • 6.5 Examples
  • 6.6 Summary
  • 7. Nonlinear Predictive Neural Control
  • 7.1 Introduction
  • 7.2 Predictive Control
  • 7.3 Nonlinear Neural Predictors
  • 7.4 Predictive Neural Control
  • 7.5 On-line Learning of Neural Predictors
  • 7.6 Sequential Predictive Neural Control
  • 7.7 An Example
  • 7.8 Summary
  • 8. Variable Structure Neural Control
  • 8.1 Introduction
  • 8.2 Variable Structure Control
  • 8.3 Variable Structure Neural Control
  • 1. Neural Networks
  • 1.1 Introduction
  • 1.2 Model of a Neuron
  • 1.3 Architectures of Neural Networks
  • 1.4 Various Neural Networks
  • 1.5 Learning and Approximation
  • 1.6 Applications of Neural Networks
  • 1.7 Mathematical Preliminaries
  • 1.8 Summary
  • 2. Sequential Nonlinear Identification
  • 2.1 Introduction
  • 2.2 Variable Neural Networks
  • 2.3 Dynamical System Modelling by Neural Networks
  • 2.4 Stable Nonlinear Identification
  • 2.5 Sequential Nonlinear Identification
  • 2.6 Sequential Identification of Multivariable Systems
  • 2.7 An Example
  • 2.8 Summary
  • 3. Recursive Nonlinear Identification
  • 3.1 Introduction
  • 3.2 Nonlinear Modelling by VPBF Networks
  • 3.3 Structure Selection of Neural Networks
  • 3.4 Recursive Learning of Neural Networks
  • 3.5 Examples
  • 3.6 Summary
  • 4. Multiobjective Nonlinear Identification
  • 4.1 Introduction
  • 4.2 Multiobjective Modelling with Neural Networks
  • 4.3 Model Selection by Genetic Algorithms

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