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Jinkun Liu - Radial Basis Function (RBF) Neural Network Control for Mechanical Systems - 9783642434556 - V9783642434556
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

€ 194.58
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Description for Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Paperback. This book introduces concrete design methods and MATLAB simulations of stable adaptive Radial Basis Function (RBF) neural control strategies. It presents a broad range of implementable neural network control design methods for mechanical systems. Num Pages: 380 pages, biography. BIC Classification: PBWH; TGMD4; TJFM; UYQ. Category: (G) General (US: Trade). Dimension: 235 x 155 x 20. Weight in Grams: 587.

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 ... Read more

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

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Product Details

Format
Paperback
Publication date
2015
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
380
Condition
New
Number of Pages
365
Place of Publication
Berlin, Germany
ISBN
9783642434556
SKU
V9783642434556
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

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