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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/77958


    Title: Fuzzy Virtual Reference Model Sensorless Tracking Control for Linear Induction Motors
    Authors: Hung, Cheng-yao;Liu, Peter;Lian, Kuang-yow
    Contributors: 淡江大學電機工程學系
    Keywords: Observers;Induction motors;Mathematical model;Force;Fuzzy logic;Tracking
    Date: 2013-06
    Issue Date: 2012-08-08 17:50:08 (UTC+8)
    Publisher: Piscataway: Institute of Electrical and Electronics Engineers
    Abstract: This paper introduces a fuzzy virtual reference model (FVRM) synthesis method for linear induction motor (LIM) speed sensorless tracking control. First, we represent the LIM as a T-S fuzzy model. Second, we estimate the immeasurable mover speed and secondary flux by a fuzzy observer. Third, to convert the speed tracking control into a stabilization problem, we define the internal desired states for state tracking via an FVRM. Finally, by solving a set of linear matrix inequalities (LMIs), we obtain the observer gains and the control gains where exponential convergence is guaranteed. The contributions of the approach in this paper are three folds: i) simplified approach -- speed tracking problem converted to stabilization problem; ii)
    omit need of actual reference model -- fuzzy virtual reference model generates internal desired states; and iii) unification of controller and observer design -- control objectives are formulated into LMI problem where powerful numerical toolboxes solve controller and observer gains. Finally, experiments are carried out to verify the theoretical results and show satisfactory performance both in transient response and robustness.
    Relation: IEEE Transactions on Cybernetics 43(3), pp.970-981
    DOI: 10.1109/TSMCB.2012.2220347
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

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