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17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)
Application of Neural Networks to Decentralized Control of Robotic Manipulators with High Degree of Freedom
Hong Kong, China
November 14-November 16
ISBN: 0-7695-2488-5
ASCII Text
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Nasser Sadati, Ehsan Elhamifar, "Application of Neural Networks to Decentralized Control of Robotic Manipulators with High Degree of Freedom," Tools with Artificial Intelligence, IEEE International Conference on, pp. 484-488, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005.
 
 
BibTex
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@article{ 10.1109/ICTAI.2005.39,
author = {Nasser Sadati and Ehsan Elhamifar},
title = {Application of Neural Networks to Decentralized Control of Robotic Manipulators with High Degree of Freedom},
journal ={Tools with Artificial Intelligence, IEEE International Conference on},
volume = {0},
year = {2005},
issn = {1082-3409},
pages = {484-488},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICTAI.2005.39},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Tools with Artificial Intelligence, IEEE International Conference on
TI - Application of Neural Networks to Decentralized Control of Robotic Manipulators with High Degree of Freedom
SN - 1082-3409
SP484
EP488
A1 - Nasser Sadati,
A1 - Ehsan Elhamifar,
PY - 2005
KW - null
VL - 0
JA - Tools with Artificial Intelligence, IEEE International Conference on
ER -
 
Nasser Sadati, Sharif University of Technology
Ehsan Elhamifar, Sharif University of Technology
In this paper a neural network decentralized control for trajectory tracking of robot manipulators is developed. The proposed decentralized control allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each subsystem are considered with unknown nonlinear bounds. The RBF neural networks (RBFNNs) are proposed to model the unknown nonlinear dynamics of the robots and the interconnection terms. Using Lyapunov method, the stability of the overall system is investigated.
Citation:
Nasser Sadati, Ehsan Elhamifar, "Application of Neural Networks to Decentralized Control of Robotic Manipulators with High Degree of Freedom," ictai, pp.484-488, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005
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