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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/74715

    Title: DSP implementation of takagi-sugeno fuzzy cerebellar model articulation controller for sensorless wind power generating systems
    Other Titles: DSP實現T-S模糊小腦模型控制器應用於無感測器風力發電系統
    Authors: 許鎵薕;Hsu, Chia-Lien
    Contributors: 淡江大學電機工程學系碩士班
    劉寅春;Liu, Peter
    Keywords: 風力發電系統;小腦模型控制器;Takagi-Sugeno模糊模組;線性矩陣不等式;Wind energy conversion system;Cerebellar model articulation controller;T-S Fuzzy Model;Linear Matrix Inequalities(LMIs)
    Date: 2011
    Issue Date: 2011-12-28 19:22:19 (UTC+8)
    Abstract: 本論文的目的是將具有永磁同步發電機(Permanent Magnet Synchronous Generator , PMSG)的風力發電系統(Wind Energy Conversion System , WECS),建置一個模糊模式控制器,以期可以達到最大功率追蹤(Maximum Power Point Tracking, MPPT)。並且,本篇論文以模糊模式小腦模型控制器與負迴授控制器整合,根據負迴授控制器決定控制輸入,並透過線性矩陣不等式(Linear Matrix Inequality , LMI)計算得到最佳控制增益,再來,將含有干擾的風力發電系統透過T-S模糊模式與虛擬變數合成設計(Virtual Desire Variable synthesis, VDVs)轉化成線性系統,並且透過小腦模型控制器學習,將系統內的狀態因為干擾而不穩定的曲線收斂在一定範圍值;再加上透過與小腦模型近似的補償控制器,降低因為小腦控制器而產生的不穩定數據濾除。
    在模擬與實現的部分,本篇論文首先透過先由MATLAB模擬驗證其控制器可得到最大功率輸出。再以dSPACE 1104整合平台並藉此做為控制器設計的依據。最後,透過連接風力發電機與可供應大電流傳輸的直流-直流電源轉換器來進行實際平台的驗證。
    This thesis proposes a maximum wind power tracking control using a
    Takagi-Sugeno fuzzy type cerebellar model articulation controller (T-S CMAC).
    The controller is designed based on cerebellar model articulation controller (CMAC)
    is used to estimate maximum wind power through CMAC which has auto-learning
    property. According to the state from wind energy conversion system (WECS), the
    controller would track the maximum power by learning more than hundred of
    thousand times. Using this controller we can find out that computation is less than
    original controller with self-learning skill, and the tracking time would be less than
    traditional controller. The effectiveness of proposed controller is performed and shown satisfactory numerical results. First, the wind energy conversion system is consider as a permanent magnet synchronous generator in series with a DC-DC convertor, we then use a T-S fuzzy representation, where a fuzzy tracking controller, CMAC controller, and compensating controller is designed. Then we use a Lyapunov stability to obtain LMIs which can be solved by Matlab’s LMI toolbox and update laws of the CMAC.
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Thesis

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