Decentralized neural control : application to robotics

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 gat...

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Bibliographic Details
Main Authors: Garcia-Hernandez, Ramon, (Author), Lopez-Franco, Michel, (Author), Sanchez, Edgar N., (Author), Alanis, Alma Y., (Author), Ruz-Hernandez, Jose A., (Author)
Format: eBook
Language: English
Published: Cham, Switzerland : Springer, 2017.
Series: Studies in systems, decision and control ; v. 96.
Subjects:
Neural networks (Computer science)
Nonlinear control theory.
elektronické knihy
electronic books
ISBN: 9783319533124
9783319533117
Physical Description: 1 online resource

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245 0 0 |a Decentralized neural control :  |b application to robotics /  |c Ramon Garcia-Hernandez, Michel Lopez-Franco, Edgar N. Sanchez, Alma Y. Alanis, Jose A. Ruz-Hernandez. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a Studies in systems, decision and control ;  |v volume 96 
504 |a Includes bibliographical references. 
505 0 |a Introduction -- Foundations -- Decentralized Neural Block Control -- Decentralized Neural Backstepping Control -- Decentralized Inverse Optimal Control for Stabilization: a CLF Approach -- Decentralized Inverse Optimal Control for Trajectory Tracking -- Robotics Application -- Conclusions. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Neural networks (Computer science) 
650 0 |a Nonlinear control theory. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Garcia-Hernandez, Ramon,  |e author. 
700 1 |a Lopez-Franco, Michel,  |e author. 
700 1 |a Sanchez, Edgar N.,  |e author. 
700 1 |a Alanis, Alma Y.,  |e author. 
700 1 |a Ruz-Hernandez, Jose A.,  |e author. 
776 0 8 |i Print version:  |t Decentralized neural control.  |d Cham, Switzerland : Springer, 2017  |z 3319533118  |z 9783319533117  |w (OCoLC)967824093 
830 0 |a Studies in systems, decision and control ;  |v v. 96. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-53312-4  |y Plný text 
992 |c NTK-SpringerENG 
999 |c 99793  |d 99793 
993 |x NEPOSILAT  |y EIZ 

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