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
收藏
页码：3040 / +
页数：3
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