Decentralized Adaptive Neural Network Control for Reconfigurable Manipulators

被引：6
|
作者：
Zhu, Lu [1 ,2 ]
Li, Yuanchun [2 ]
机构：
[1] Jilin Univ, State Key Lab Automobile Dynam Simulat, Changchun 130022, Peoples R China
[2] Jilin Univ, Dept Commun Engn, Changchun 130022, Peoples R China
来源：
2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5 | 2010年
基金：
中国国家自然科学基金;
关键词：
Reconfigurable Manipulators; Decentralized Control; Neural Networks; Adaptive Control; Backstepping Design; OUTPUT-FEEDBACK CONTROL; NONLINEAR-SYSTEMS; ROBOT MANIPULATORS;
D O I：
10.1109/CCDC.2010.5498523
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a decentralized adaptive neural network control algorithm for reconfigurable manipulators based on Lyapunov's stability analysis and backstepping techniques is proposed. The dynamics of reconfigurable manipulators is represented as a set of interconnected subsystems. Neural networks are used to approximate the unknown dynamic functions and interconnections in the subsystems by using adaptive algorithm. The effectiveness of the proposed scheme is demonstrated by computer simulations.
引用
收藏
页码：1760 / +
页数：3
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