Title :
Application of neural networks to decentralized control of robot manipulators with high degree of freedom
Author :
Sadati, Nasser ; Elhamifar, Ehsan
Author_Institution :
Intelligent Syst. Lab., Sharif Univ. of Technol., Tehran
Abstract :
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
Keywords :
Lyapunov methods; closed loop systems; decentralised control; manipulator dynamics; neurocontrollers; position control; radial basis function networks; stability; Lyapunov method; RBF neural network; closed-loop system; degree of freedom; neural network decentralized control; nonlinear dynamics; robot manipulator dynamics; system stability; trajectory tracking; uniformly ultimately boundedness; Distributed control; Error correction; Lyapunov method; Manipulator dynamics; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Robots; Stability; Trajectory;
Conference_Titel :
Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2488-5
DOI :
10.1109/ICTAI.2005.39
