Sliding Mode Control Using MATLAB - 10 Angebote vergleichen
| Preise | Juni 17 | Juli 17 | Okt. 17 | Jan. 18 |
|---|---|---|---|---|
| Schnitt | € 127,51 | € 125,37 | € 124,94 | € 128,58 |
| Nachfrage |
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Radial Basis Function (Rbf) Neural Network Control for Mechanical Systems (2015)
DE NWISBN: 9783642434556 bzw. 364243455X, in Deutsch, Springer, neu.
Von Händler/Antiquariat, PBShop [61989342], Secaucus, NJ, U.S.A.
New Book.Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000.
New Book.Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000.
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems
~EN PB NWISBN: 9783642434556 bzw. 364243455X, vermutlich in Englisch, Springer Shop, Taschenbuch, neu.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Lagernd, zzgl. Versandkosten.
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. Soft cover.
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. Soft cover.
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| Radial Basis Function (RBF) Neural Network Control for Mechanical Systems | Springer | 2013 | 2015
~EN NWISBN: 9783642434556 bzw. 364243455X, vermutlich in Englisch, Springer, neu.
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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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems
~EN NW ABISBN: 9783642434556 bzw. 364243455X, vermutlich in Englisch, Springer, Berlin/Heidelberg/New York, NY, Deutschland, neu, Hörbuch.
Lieferung aus: Niederlande, Lieferzeit: 5 Tage, zzgl. Versandkosten.
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 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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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems - Design, Analysis and Matlab Simulation
~EN PB NWISBN: 9783642434556 bzw. 364243455X, vermutlich in Englisch, Springer Berlin Heidelberg, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: 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. Englisch, Taschenbuch.
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: 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. Englisch, Taschenbuch.
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Sliding Mode Control Using MATLAB (2017)
EN NW FE EB DLISBN: 9780128026700 bzw. 0128026707, in Englisch, 346 Seiten, Academic Press, neu, Erstausgabe, E-Book, elektronischer Download.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, ebook for download, Free shipping.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
7
Sliding Mode Control Using MATLAB (2017)
EN NW FE EB DLISBN: 9780128026700 bzw. 0128026707, in Englisch, 346 Seiten, Academic Press, neu, Erstausgabe, E-Book, elektronischer Download.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, E-Book zum Download, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
8
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems (2013)
~EN PB NWISBN: 364243455X bzw. 9783642434556, vermutlich in Englisch, Springer Berlin Heidelberg, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
9
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems (2013)
~EN NWISBN: 364243455X bzw. 9783642434556, vermutlich in Englisch, Springer, Berlin/Heidelberg/New York, NY, Deutschland, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
10
Radial Basis Function (RBF) Neural Network Control f (2015)
~EN HC NWISBN: 9783642434556 bzw. 364243455X, vermutlich in Englisch, Springer, Berlin/Heidelberg/New York, NY, Deutschland, gebundenes Buch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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