Description

This book 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, etc.).

Differential Neural Networks For Robust Nonlinear Control: Identification, State Estimation And Trajectory Tracking

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£174.00

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Hardback by Alex Poznyak , Edgar N Sanchez

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This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control... Read more

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 08/10/2001
    ISBN13: 9789810246242, 978-9810246242
    ISBN10: 9810246242

    Number of Pages: 456

    Non Fiction , Technology, Engineering & Agriculture , Education

    Description

    This book 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, etc.).

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