Neural-network-based robot time-varying force control with uncertain manipulator-environment system

被引：21

作者：

Xu, Wenkang ^{[1
]}

Cai, Chenxiao ^{[1
]}

Zou, Yun ^{[1
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China

来源：

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL | 2014年 / 36卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Time-varying force tracking; robot force control; robust control; neural network; DYNAMICS; TRACKING;

D O I：

10.1177/0142331214528971

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper considers the problem of time-varying force control for robot manipulators in the presence of uncertainties from both the robotic model and working environment. The position-based impedance control (PBIC) method is employed and in order to achieve accurate time-varying force tracking, an improved PBIC is proposed. A neural-network-based robust controller is proposed to compensate for the system uncertainties, and an adaptive law is developed to identify the uncertain environmental parameters. Simulation results on a two-link robot manipulator confirm the effectiveness of the method in achieving time-varying force tracking.

引用

页码：999 / 1009

页数：11

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