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http://dx.doi.org/10.5302/J.ICROS.2002.8.2.113

FLNN-Based Friction Compensation Controller for XY Tables  

Chung, Chae-Wook (안산공과대학 전자통신과)
Kim, Young-Ho (한국국방연구원)
Kuc, Tae-Yong (성균관대학교 전전컴공학부)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.8, no.2, 2002 , pp. 113-119 More about this Journal
Abstract
An FLNN-based neural network controller is applied to precise positioning of XY table with friction as the extension study of [11]. The neural network identifies the frictional farces of the table. Its weight adaptation rule, named the reinforcement adaptive learning rule, is derived from the Lyapunov stability theory. The experimental results with 2-DOF XY table verify the effectiveness of the proposed control scheme. It is also expected that the proposed control approach is applicable to a wide class of mechanical systems.
Keywords
friction compensation; intelligent control; neural networks; reinforcement teaming; XY table;
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