淡江大學機構典藏:Item 987654321/104572
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    题名: Sensorless wind energy conversion system maximum power pointtracking using Takagi–Sugeno fuzzy cerebellar model articulation control
    作者: Peter Liu;Wen-Tsung Yang;Chang-En Yang;Chia-Lien Hsu
    关键词: WECS;CMAC;T-S fuzzy;Linear matrix inequalities
    日期: 2015-04
    上传时间: 2016-01-06 11:03:30 (UTC+8)
    摘要: In this paper, we propose a sensorless wind energy conversion system (WECS) maximum wind power point tracking using Takagi–Sugeno fuzzy cerebellar model articulation control (T-S CMAC). The main objective of the WECS is to achieve maximum power transfer under various wind speeds without actual measurement of the wind velocity. We first represent the WECS, which uses a permanent magnet synchronous generator (PMSG), as a nonlinear dynamical model. To carry out the T-S CMAC design, we rewrite the WECS model as a T-S fuzzy representation. The T-S CMAC design is inspired by the architectural similarity of the T-S fuzzy control and CMAC where accordingly the PDC design control gains and weighting parameter are augmented into a single vector. The advantages of this approach are 3-fold: (i) increases accuracy of CMAC initial weights – we assign the initial weights of CMAC using the control gains solved by the LMIs from the PDC design; (ii) introduces adaptive ability in LMI-based design – the CMAC design allows time-varying parameters in the system; and (iii) relaxes assumption on system uncertainty – we drop the assumption that a strict upper bound on system uncertainty is known. Numerical simulations under various wind speeds show exponential convergence results which further verify the theoretical derivations.
    關聯: Applied Soft Computing 29, p.450-460
    DOI: 10.1016/j.asoc.2015.01.019
    显示于类别:[電機工程學系暨研究所] 期刊論文

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