Sensorless wind energy conversion system maximum power pointtracking using Takagi–Sugeno fuzzy cerebellar model articulation control | |
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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 | en |
ISSN | 1872-9681; 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 | NLD |
公開徵稿 | |
出版型式 | ,電子版,紙本 |
相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/104572 ) |