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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/103667

    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:[電機工程學系暨研究所] 會議論文

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