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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/38737

    Title: 結合基因演算法與滑動模式控制設計電力系統穩定器
    Other Titles: Power System Dynamic Stabilizer Design via Combining Genetic Algorithm and Sliding Mode Control
    Authors: 張志翰;李金譚;林佩宜;黃聰亮
    Contributors: 淡江大學電機工程學系
    Keywords: 電力系統穩定器;遺傳演算法;滑動模式控制;最佳降階模型;Power System Stabilizer;Genetic Algorithm;Sliding Mode Control;Optimal Reduced Order Model
    Date: 2002-12
    Issue Date: 2010-01-11 15:48:07 (UTC+8)
    Abstract: 本文提出利用結合基因演算法與滑動模式控制來設計電力系統穩定器。電力系統穩定器可利用最佳線性調整來設計,但利用此方法會造成設計上的耗費及減少可靠度。因此,我們提出只利用需要的狀態變數之控制設計,如角頻率及轉矩角。為了解決這些設計上的問題,我們使用最佳降階法將發電機降階成兩狀態變數矩陣,利用基因演算法尋找切換平面向量與回授增益向量,再利用滑動模式控制尋找發電機的控制信號,並配合最佳降階式設計,應用此方法於單機無限匯流排電力系統,模擬此結果並舉出其優點。
    This thesis proposes a new approach for combining genetic algorithm and sliding mode control to design the power system stabilizers (PSS). The design of a PSS can be formulated as an optimal linear regulator control problem. However, implementing this technique requires the design of estimators. This increases the implementation and reduces the reliability of control system. These reasons, therefore, favor a control scheme that uses only some desired state variables, such as torque angle and speed. To deal with this problem, we use the optimal reduced models to reduce the power system model into two state variables system by each generator. We use the genetic algorithm to find the switching surface vector and switching control signals and use sliding mode control to find control signal of the generator. Finally, the advantages of the proposed method are illustrated by numerical simulation of the one machines-infinite-bus power systems.
    Relation: 2002中華民國第十屆模糊理論及其應用會議論文集=Proceedings of 2002 Tenth National Conference on Fuzzy Theory and It's Applications,頁41280
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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