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Decentralized Neural Backstepping Control Applied to a Robot Manipulator : Controllo neurale retroattivo decentralizato applicato a un manipolatore robotico, in: International Journal of Advanced Robotic Systems

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Autor Garcia-Hernandez, Ramon; Ruz-Hernandez, Jose A.; Rullan-Lara, Jose L.
Publicado  InTech Open Access Publisher, 2013
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Abstract This paper presents a discrete‐time
decentralized control scheme for trajectory tracking of a
two degrees of freedom (DOF) robot manipulator. A high
order neural network (HONN) is used to approximate a
decentralized control law designed by the backstepping
technique as applied to a block strict feedback form
(BSFF). The weights for each neural network are adapted
online by an extended Kalman filter training algorithm.
The motion for each joint is controlled independently
using only local angular position and velocity
measurements. The stability analysis for the closed‐loop
system via the Lyapunov approach is included. Finally,
the real‐time results show the feasibility of the proposed
control scheme using a robot manipulator.
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no fulltext found International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publicado: 2004
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Documents: International Journal of Advanced Robotic Systems
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DMG-Lib FaviconDMG-Lib https://www.dmg-lib.org/dmglib/handler?docum=32416009
Europeana FaviconEuropeana  http://www.europeana.eu/portal/record/2020801/dmglib_handler_docum_32416009.html
PDF FaviconPDF  Decentralized Neural Backstepping Control Applied to a Robot Manipulator
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Time of publication 2013
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License

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