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Radial Basis Function Rbf Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation - Rilegato
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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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Edizione Internazionale
Radial Basis Function Neural Network Control for Mechanical Systems, Hardcover edition
Edizione InternazionaleDa: Sizzler Texts, SAN GABRIEL, CA, U.S.A.
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Hardcover. Condizione: New. Condizione sovraccoperta: New. 1st Edition. **INTERNATIONAL EDITION** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments go through via USPS/UPS/DHL with tracking numbers. Great professional textbook selling experience and expedite shipping service. Codice articolo ABE-10806887557
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Edizione Internazionale
Radial Basis Function (Rbf) Neural Network Control for Mechanical Systems: Design, Analysis and MATLAB Simulation, Hardcover
Edizione InternazionaleDa: Aideo Books, San Marino, CA, U.S.A.
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Hardcover. Condizione: New in new dust jacket. First edition. 2013 ed. ***INTERNATIONAL EDITION*** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments contain tracking numbers. Great professional textbook selling experience and expedite shipping service. Sewn binding. Cloth over boards. 365 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color. Audience: General/trade. Codice articolo K186H0000483
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Radial Basis Function (rbf) Neural Network Control For Mechanical Systems
Da: Basi6 International, Irving, TX, U.S.A.
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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Codice articolo ABEJUNE24-272387
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Radial Basis Function (rbf) Neural Network Control For Mechanical Systems
Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
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Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Codice articolo ABNR-90575
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems : Design, Analysis and Matlab Simulation
Editore:
Springer Berlin Heidelberg, 2013
ISBN 10: 3642348157
ISBN 13: 9783642348150
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Da: Buchpark, Trebbin, Germania
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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 384 | Sprache: Englisch | Produktart: Bücher. Codice articolo 23189497/12
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems
Print on DemandDa: moluna, Greven, Germania
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fundamental and thorough understanding in the neural network control system design Typical adaptive RBF neural controllers design and stability analysis are given in a concise manner Many engineering application examples for mechanical syst. Codice articolo 5057743
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation
Da: HPB-Red, Dallas, TX, U.S.A.
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hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Codice articolo S_420366572
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Radial Basis Function Rbf Neural Network Control for Mechanical Systems : Design, Analysis and Matlab Simulation
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Condizione: New. Codice articolo 19074854-n
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems
Editore:
Springer Berlin Heidelberg Jan 2013, 2013
ISBN 10: 3642348157
ISBN 13: 9783642348150
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 384 pp. Englisch. Codice articolo 9783642348150
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems : Design, Analysis and Matlab Simulation
Da: AHA-BUCH GmbH, Einbeck, Germania
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783642348150
Quantità: 1 disponibili