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World Scientific Publishing Company World Scientific Differential Neural Networks Control Book

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Description

Explore advanced control theory with Differential Neural Networks for Robust Nonlinear Control. Published by World Scientific Publishing Company, this book examines continuous time dynamic neural networks and their application to solving fundamental problems in robust control. The text covers essential topics such as identification, state space estimation via neuro-observers, and trajectory tracking. It is designed for scenarios where plants are a priori unknown and contain internal unmodelled dynamics or external perturbations. Readers will find detailed error stability analysis and specific error bounds for various problems. This resource provides a technical foundation for understanding how neural network theory applies to complex, real-world nonlinear control systems.

Key Features

Covers continuous time dynamic neural networks theory for solving basic problems in robust control theory.

Provides detailed methods for identification, state space estimation using neuro-observers, and trajectory tracking.

Addresses control of plants that are a priori unknown and contain internal unmodelled dynamics.

Includes error stability analysis and corresponding error bounds for different control problems.

Discusses handling of external perturbations within the context of nonlinear control systems.

Published by World Scientific Publishing Company for technical accuracy in AI and machine learning.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
01 October 2001
Listed Since
15 December 2006

Barcode

No barcode data available

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