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    Title: Maximum power point tracking for the proton exchange membrane fuel cell via T-S CMAC control
    Other Titles: 使用T-S CMAC之質子交換膜燃料電池最大功率追蹤控制
    Authors: 林舁曜;Lin, Yu-Yao
    Contributors: 淡江大學電機工程學系碩士班
    劉寅春;Liu, Peter
    Keywords: 質子交換膜燃料電池;最大功率追蹤;T-S模糊;線性矩陣不等式;小腦模型控制器;PEM fuel cell;maximum Power point tracking;T-S fuzzy;Linear matrix inequalities;CMAC
    Date: 2013
    Issue Date: 2014-01-23 14:45:07 (UTC+8)
    Abstract: 本論文提出一種使用T-S模糊小腦模型控制器實現PEM燃料電池最大功率追蹤控制。T-S模糊小腦模型(T-S CMAC)的設計來自於PDC控制增益和權重值組合成一個個別的單一向量擴充與T-S模糊理論和CMAC理論相似。此控制器有以下優點:
    一、使用LMI求解出控制增益,故可以提升CMAC初始權重的準確性。
    二、 LMI引用自適應能力的CMAC設計,允許有時變參數在系統中。
    三、可以快速並且反覆的學習修正控制量。
    由結果可得知T-S模糊小腦模型(T-S CMAC)可以有效的達成最大功率追蹤之目的,提升燃料電池之效能,減少能源的損耗。
    This paper presents a T-S CMAC controller implement PEM fuel cell maximum power tracking control. T-S CMAC is designed from the PDC control gain and weight values combined into a single vector of individual expansion with T-S fuzzy theory
    and CMAC theory of similarity. The controller has the following advantages i.) Using LMI solved control gain and it can improve the accuracy of the CMAC initial weight.
    ii.) LMI quote adaptive ability design the CMAC that allows time-varying parameters in the system. iii.) Can quickly and repeatedly learning correction amount of control. From the results T-S CMAC can effectively accomplish the purpose of the maximum power point tracking. Improve the effectiveness of fuel cells and can reduce energy consumption.
    Appears in Collections:[電機工程學系暨研究所] 學位論文

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