Decentralized Neural Control: Application to Robotics: 96 (Studies in Systems, Decision and Control) - Tapa blanda

Libro 85 de 378: Studies in Systems, Decision and Control

Garcia-Hernandez, Ramon; Lopez-Franco, Michel; Sanchez, Edgar N.; Alanis, Alma Y.; Ruz-Hernandez, Jose A.

 
9783319851235: Decentralized Neural Control: Application to Robotics: 96 (Studies in Systems, Decision and Control)
Tapa blanda
ISBN 10: 3319851233 ISBN 13: 9783319851235
Editorial: Springer, 2018

Sinopsis

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. 

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2018
Idioma
Inglés
ISBN 10 
3319851233
ISBN 13 
9783319851235
Encuadernación
Tapa blanda
Número de páginas
128
Contacto del fabricante
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Alemania

Otras ediciones populares con el mismo título

9783319533117: Decentralized Neural Control: Application to Robotics: 96 (Studies in Systems, Decision and Control, 96)

Edición Destacada

ISBN 10:  3319533118 ISBN 13:  9783319533117
Editorial: Springer, 2017
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