Fuzzy-neuro position/force control of robot manipulators with uncertainties

被引：0
|
作者：
Wei, LX [1 ]
Yang, L [1 ]
Wang, HR [1 ]
机构：
[1] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Peoples R China
来源：
PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3 | 2005年
关键词：
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：
In this paper, a new robust robot force tracking impedance control scheme that has the capability to track a specified desired force and to compensate for uncertainties in environment stiffness as well as in robot dynamic model is proposed. The uncertainties in robot dynamics are compensated by a radial basis function network (RBFN) controller, and a fuzzy tuning mechanism is developed to generate the impedance model which describes the relationship between force and position/velocity error. Simulation studies based on a two-DOF robot manipulator are carried out and the results show that highly robust position/force tracking can be achieved in the presence of large uncertainties.
引用
收藏
页码：1004 / 1008
页数：5
相关论文
共 50 条
12345