Self-organizing fuzzy sliding-mode control for a voice coil motor

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Title:	Self-organizing fuzzy sliding-mode control for a voice coil motor
Authors:	許駿飛;Kai-Yi Wong
Keywords:	fuzzy control;gradient methods;learning (artificial intelligence);self-adjusting systems;variable structure systems
Date:	2015-04-09
Issue Date:	2015-09-15 15:44:06 (UTC+8)
Publisher:	IEEE
Abstract:	Voice coil motor (VCM) is widely known as its topquality of free friction, low noise, fast transient response and well repeatability. Yet the dynamic characteristic of a VCM is nonlinear and time-varying, thus the model-based conventional controller is difficult to achieve high-precision control performance for a VCM. To attack this problem, a selforganizing fuzzy sliding-mode control (SFSC) system is proposed in this paper. All of the fuzzy rules are online grown and pruned by the structure learning phase and the parameter learning phase is designed to tune the controller parameter in the gradient-descent-learning algorithm. From the experiment results, it shows that the proposed SFSC system can successfully control a VCM with favorable control response with enhanced disturbance rejection performance.
Relation:	12th IEEE International Conference on Networking, Sensing and Control, pp.287-292
DOI:	10.1109/ICNSC.2015.7116050
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Proceeding

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