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
收藏
页码：999 / 1009
页数：11
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