A neural network-based learning controller for micro-sized object micromanipulation

被引：0

作者：

Shahini, Mohsen ^{[1
]}

Melek, William W. ^{[1
]}

Yeow, John T. W. ^{[2
]}

机构：

[1] Univ Waterloo, Dept Mech Engn, Waterloo, ON N2L 3G1, Canada

[2] Univ Waterloo, Dept Syst Design Engn, Waterloo, ON N2L 3G1, Canada

来源：

2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6 | 2007年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, automated micro-sized objects manipulation is investigated. The novelty of the proposed method lies on the compensation of all the nonlinear scaling forces which are dominant over gravitational force. A dynamic neural network has been added to a PD conventional controller for automated micromanipulation control. Weight-updating rules have been obtained in such a way that the system is uniformly ultimately bounded (UUB) in the sense of Lyapunov. Simulation results for controlled pushing of a micro-object have been illustrated and the efficiency of the method has been shown by comparing its result with that of a linear controller.

引用

页码：3040 / +

页数：3

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