Decentralized neural network control for guaranteed tracking error constraint of a robot manipulator

被引：0
作者：
Seong-Ik Han
Jang-Myung Lee
机构：
[1] Pusan National University,Department ofElectronic Engineering
来源：
International Journal of Control, Automation and Systems | 2015年 / 13卷
关键词：
Constrained error variable; decentralized control; prescribed performance function; RBF network; robot manipulator;
D O I：
暂无
中图分类号：
学科分类号：
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.
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页码：906 / 915
页数：9
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