Radial basis function network-based adaptive tracking control for robot manipulators

被引：0
|
作者：
Wang, HR [1 ]
Zhu, QG [1 ]
Chen, Y [1 ]
机构：
[1] Hebei Univ, Inst Elect & Commun Engn, Baoding 071002, Peoples R China
来源：
PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2004年
关键词：
robot manipulators; RBF network; adaptive control; sliding model control;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A Radial Basis Function (RBF) network-based adaptive tracking control scheme is proposed for robot manipulators. A RBF network is used to generate control input signals that are similar to the control inputs of adaptive control using liner reparameterization of the robot manipulator. A sliding model control term is used to eliminate the effects of the network inherent approximation errors and external disturbance. The asymptotic stability of the control system is established using Lyapunov theorem. Simulations are given for a two-link robot in the end of the paper, and validate the control arithmetic.
引用
收藏
页码：510 / 514
页数：5
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