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研究生： 王昇龍
Sheng-Lung Wang
論文名稱： 智慧型控制數位化串聯諧振轉換器之研製
Design and Implementation of DSP-based Intelligent Control for Series Resonant Converter
指導教授： 林法正
Faa-Jeng Lin
薛木添
Muh-Tian Shiue
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 電機工程學系
Department of Electrical Engineering
論文出版年： 2013
畢業學年度： 101
語文別： 中文
論文頁數： 121
中文關鍵詞： 機率型模糊類神經網路 、對稱歸屬函數之TSK機率模糊類神經網路 、數位訊號處理器 、串聯諧振轉換器
外文關鍵詞： probabilistic fuzzy neural network, TSK-type probabilistic fuzzy neural network with asymmetric membership function, digital signal processor, series resonant converter
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    • 本論文目的為研製以數位訊號處理器為基礎之智慧型控制串聯諧振轉換器，其中串聯諧振電路採用LLC架構。在LLC架構中，是以固定50%責任週期之互補訊號驅動功率晶體，並藉由調變頻率使變壓器一次側之漏電感、激磁電感、諧振電容以及開關上的寄生元件產生諧振，達到零電壓切換來降低元件的切換損失，且在變壓器二次側整流電路使用同步整流功能，以功率開關取代二極體來減少導通損失進而提升系統效率。為了改善輸出電壓在負載調節時的暫態響應，本文提出兩種智慧型控制器取代比例積分控制器，一個是機率型模糊類神經網路，另一個是非對稱歸屬函數之TSK機率模糊類神經網路。本文將詳細介紹機率型模糊類神經網路以及非對稱歸屬函數之TSK機率模糊類神經網路控制器之網路架構、線上學習法則以及收斂性分析。最後透過實驗結果來驗證其可行性。

    The purpose of this thesis is to develop a digital signal processor (DSP) based intelligent control of series resonant converter (SRC). The SRC is constructed using LLC resonant tank which is driven by a half-bridge circuit with fixed 50%-duty carrier frequency. The resonant phenomenon can be obtained by using of the leakage inductance of primary coil, the magnetizing inductance of the transformer, the resonant capacitor and parasitic component of power MOSFETs. Moreover, the zero-voltage-switching (ZVS) can be achieved using resonant phenomenon to reduce the switching loss. Furthermore, the synchronous rectifier is added in the secondary side of transformer by using the power MOSFETs in place of the diode to reduce the conduction loss. In addition, to improve the transient response of the voltage regulation during load variation, two intelligent controls are proposed. One is the probabilistic fuzzy neural network (PFNN), and the other is the TSK-type probabilistic fuzzy neural network with asymmetric membership function (TSKPFNN-AMF). The network structures, online learning algorithms and convergence analyses of the PFNN and the TSKPFNN-AMF controls are introduced in detail. Finally, the feasibility of the proposed control schemes are verified through experimentation.

    中文摘要 I 英文摘要 II 目錄 III 圖目錄 VI 表目錄 X 第一章 緒論 1 1.1 研究動機與目的 1 1.2 研究背景 3 1.3 論文大綱 7 1.4 論文貢獻 8 第二章 串聯諧振轉換器原理分析及數位訊號處理器 10 2.1 前言 10 2.2 串聯諧振電路 10 2.3 半橋串聯諧振轉換器之電路分析 12 2.4 半橋串聯諧振轉換器電路動作原理 14 2.5 串聯諧振轉換器之同步整流及達到零電壓切換的條件 23 2.6 串聯諧振轉換器之輕載輸出電壓調控 26 2.7 半橋串聯諧振轉換器之設計 28 2.7.1 功率晶體之選擇 30 2.7.2 諧振槽元件設計 31 2.7.3 變壓器設計 33 2.7.4 輸出電容設計 36 2.7.5 串聯諧振轉換器之數位控制 37 2.7.6 數位訊號處理器之類比數位保護電路 38 2.7.7 電壓回授硬體電路 39 2.8 數位訊號處理器TMS320F28035 40 2.8.1 數位訊號處理器TMS320F28035功能簡介 40 2.8.2 記憶體規劃 41 2.9 週邊功能介紹 43 2.9.1 增強型脈波寬度調變模組 43 2.9.2 中斷處理之流程 45 2.9.3 類比/數位轉換器 46 2.9.4 串列週邊介面模組 47 2.9.5 串列傳輸介面模組 49 2.10 實驗結果 50 第三章 機率型模糊類神經網路控制 55 3.1 簡介 55 3.2 機率型模糊類神經網路架構 55 3.3 線上學習法則 59 3.4 收斂性分析 61 3.5 軟體架構 62 3.6 實驗結果 63 第四章 非對稱歸屬函數之TSK機率模糊類神經網路控制 67 4.1 簡介 67 4.2 非對稱歸屬函數之TSK機率模糊類神經網路架構 67 4.3 線上學習法則 71 4.4 收斂性分析 74 4.5 軟體架構 76 4.6 實驗結果 77 第五章 頻率響應分析 81 5.1 前言 81 5.2 比例積分控制系統設計 81 5.3 比例積分控制系統模擬與實驗 83 5.4 智慧型控制系統實驗 85 第六章 結論與未來展望 90 6.1 結論 90 6.2 未來展望 90 參考文獻 91 附錄 電力線通訊 99 1 簡介 99 2 串列傳輸/乙太網路轉換 100 3 電力線/乙太網路轉換 101 3.1 Atheros Intellon 6400晶片組 103 4 實驗結果 104

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