Differential Neural Networks for Robust Nonlinear Control: Identification, State Estimation and Trajectory Tracking

✍ Scribed by Alexander S. Poznyak, Edgar N. Sanchez, Wen Yu

Publisher: World Scientific Publishing Company
Year: 2001
Tongue: English
Leaves: 454
Edition: 1st
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This volume deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical).

✦ Table of Contents

Differential Neural Networksfor Robust Nonlinear Control......Page 4
Preface......Page 8
Acknowledgments......Page 10
Contents......Page 12
List of Figures......Page 18
Introduction......Page 24

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