Fuzzy Adaptation Algorithms' Control for Robot Manipulators with Uncertainty Modelling Errors

被引：5

作者：

Fan, Yongqing ^{[1
,2
]}

Xing, Keyi ^{[1
,2
]}

Jiang, Xiangkui ^{[3
]}

机构：

[1] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Shaanxi, Peoples R China

[2] Xi An Jiao Tong Univ, Syst Engn Inst, Xian 710049, Shaanxi, Peoples R China

[3] Xian Univ Posts & Telecommun, Sch Automat, Xian, Shaanxi, Peoples R China

来源：

COMPLEXITY | 2018年

基金：

中国国家自然科学基金;

关键词：

ADAPTIVE-CONTROL; TRACKING CONTROL; FORCE FEEDBACK; DESIGN; SYSTEMS; APPROXIMATION; PERFORMANCE; OBSERVER;

D O I：

10.1155/2018/5468090

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators' system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a referencemodel dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example.

引用

页数：8

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