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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Autorzy
Wydawnictwo Springer Nature
Data wydania 26/01/2013
Forma publikacji eBook: Reflowable eTextbook (ePub)
Język angielski
ISBN 9783642348167
Kategorie Matematyka stosowana, Inżynieria: pojęcia ogólne, Inżynieria mechaniczna i materiałowa, Inżynieria automatyki, Sztuczna inteligencja
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Typ przesyłki: wysyłka kodu na adres e-mail
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Opis książki

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.

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

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