Decentralized Neural Control: Application to Robotics: 96 (Studies in Systems, Decision and Control, 96) - Softcover
This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network.The third control scheme applies a decentralized neural inverse optimal control for stabilization. The fourth decentralized neural inverse optimal control is designed for trajectory tracking. This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work.
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- PublisherSpringer
- Publication date2018
- ISBN 10 3319851233
- ISBN 13 9783319851235
- BindingPaperback
- Number of pages126
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Decentralized Neural Control: Application to Robotics (Studies in Systems, Decision and Control, 96)
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Book Description Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors.This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF).The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold.The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network.The third control scheme applies a decentralized neural inverse optimal control for stabilization.The fourth decentralized neural inverse optimal control is designed for trajectory tracking.This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work. 111 pp. Englisch. Seller Inventory # 9783319851235
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Decentralized Neural Control: Application to Robotics
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Book Description Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent research in decentralized neural controlIncludes applications to roboticsPresents results in simulation and real timeThis book provides a decentralized approach for the identification and control of robotics syste. Seller Inventory # 458625439
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Book Description Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors.This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF).The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold.The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network.The thirdcontrol scheme applies a decentralized neural inverse optimal control for stabilization.The fourth decentralized neural inverse optimal control is designed for trajectory tracking.This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work. Seller Inventory # 9783319851235
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Book Description Condition: New. 2018. Softcover reprint of the original 1st ed. 2017. paperback. . . . . . Books ship from the US and Ireland. Seller Inventory # V9783319851235
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