Decentralized Neural Network Control for Guaranteed Tracking Error Constraint of a Robot Manipulator

被引：18

作者：

Han, Seong-Ik ^{[1
]}

Lee, Jang-Myung ^{[1
]}

机构：

[1] Pusan Natl Univ, Dept Elect Engn, Busan 609735, South Korea

来源：

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2015年 / 13卷 / 04期

基金：

新加坡国家研究基金会;

关键词：

Constrained error variable; decentralized control; prescribed performance function; RBF network; robot manipulator; SLIDING MODE CONTROL; FINITE-TIME CONTROL; MOTION/FORCE CONTROL; SYSTEMS;

D O I：

10.1007/s12555-014-0132-2

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 new constrained error variable similar to sliding mode surface (SMC) is proposed to ensure a prescribed position tracking performance of a robot manipulator. A decentralized controller using this constrained error variable and a radial basis function network (RBF) is designed. The proposed decentralized and constrained control system ensures a prescribed transient and steady-state time positioning performance of the decentralized manipulator components without violation of the prescribed performance. The effectiveness of the proposed decentralized and robust control scheme was determined by comparing the results of simulated and experimental evaluation with the conventional SMC and finite-time terminal SMC methods.

引用

页码：906 / 915

页数：10

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