Robot discrete adaptive control based on dynamic inversion using dynamical neural networks

被引：31

作者：

Sun, FC ^{[1
]}

Li, HX

Li, L

机构：

[1] Tsing Hua Univ, Dept Comp Sci & Technol, State Key Lab Intelligent Technol & Syst, Beijing 100084, Peoples R China

[2] City Univ Hong Kong, Dept Mfg Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China

[3] Chinese Acad Sci, Inst Software, Beijing 100080, Peoples R China

来源：

AUTOMATICA | 2002年 / 38卷 / 11期

基金：

中国国家自然科学基金;

关键词：

neural networks; dynamic inversion; adaptive control; manipulators; variable structures;

D O I：

10.1016/S0005-1098(02)00116-4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A stable discrete time adaptive control approach using dynamic neural networks (DNNs) is developed in this paper for the trajectory tracking of a robotic manipulator with unknown nonlinear dynamics. By using dynamic inversion constructed by a DNN, the assumption under which the system state should be on a compact set can be removed. This assumption is usually required in neuro-adaptive control. The NN-based variable structure control is designed to guarantee the stability and improve the dynamic performance of the closed-loop system. The proposed control scheme ensures the global stability and desired tracking as well. (C) 2002 Elsevier Science Ltd. All rights reserved.

引用

页码：1977 / 1983

页数：7

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