教師資料查詢 | 類別: 期刊論文 | 教師: 劉寅春 Peter Liu (瀏覽個人網頁)

標題：Sensorless wind energy conversion system maximum power pointtracking using Takagi–Sugeno fuzzy cerebellar model articulation control
學年103
學期2
出版（發表）日期2015/04/01
作品名稱Sensorless wind energy conversion system maximum power pointtracking using Takagi–Sugeno fuzzy cerebellar model articulation control
作品名稱（其他語言）
著者Peter Liu; Wen-Tsung Yang; Chang-En Yang; Chia-Lien Hsu
單位
出版者
著錄名稱、卷期、頁數Applied Soft Computing 29, p.450-460
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.
關鍵字WECS;CMAC;T-S fuzzy;Linear matrix inequalities
語言英文
ISSN1872-9681; 1568-4946
期刊性質國外
收錄於SCI;
產學合作
通訊作者
審稿制度否
國別荷蘭
公開徵稿
出版型式,電子版,紙本
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