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Radial Basis Function (Rbf) Neural Network Control for Mechanical Systems, Hardcover

Jinkun Liu

ISBN 10: 3642348173 / ISBN 13: 9783642348174
Editorial: Springer, 2013
Nuevos Condición: New Encuadernación de tapa dura
Librería: Greenland Texts (Mongkok, KL, Hong Kong)

Librería en AbeBooks desde: 30 de mayo de 2012

Cantidad: > 20

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Low price guarantee! The book is the brand new international edition textbook with the different ISBN and cover design. The book main content black/white printed in full English as same as the corresponding original US edition. Fast shipments in one to two working days after the orders confirmed. N° de ref. de la librería ABE-10806887537

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Detalles bibliográficos

Título: Radial Basis Function (Rbf) Neural Network ...

Editorial: Springer

Año de publicación: 2013

Encuadernación: Hardcover

Condición del libro:New

Condición de la sobrecubierta: New

Edición: 1st Edition

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Sinopsis:

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design.
 
This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation.

Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.

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