Compensating Dynamics of Impedance Haptic Devices Using Neural Networks

被引：1

作者：

Melinte, Octavian ^{[1
]}

Munteanu, Radu ^{[2
]}

Gal, Ioan Alexandru ^{[1
]}

Vladareanu, Luige ^{[1
]}

机构：

[1] Romanian Acad, Inst Solid Mech, Bucharest, Romania

[2] Tech Univ, Cluj Napoca, Romania

来源：

2013 8TH INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING (ATEE) | 2013年

关键词：

Robot control; haptic interface; intelligent control methods; Neural Networks;

D O I：

10.1109/ATEE.2013.6563539

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a Neural Network approach to compensate dynamic terms, friction force in particular, of a four degree of freedom haptic device manipulator similar to commercial one's that are on the market, which is controlled in impedance. The friction force model is analyzed using a general compensation method after which a trained Multi-Layer Neural Network is introduced in order to obtain a more accurate friction approximation for cancelling out this term from dynamics so that the movement of the device feels free and unconstraint.

引用

页数：6

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