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研究生： 楊政和
Cheng-Ho Yang
論文名稱： 具模糊類神經網路控制之新型變流器於整流性負載之應用
The Application of a Novel Inverter with Fuzzy Neural Network Control for Rectifier Loads
指導教授： 陳南鳴
Nan-Ming Chen
江炫樟
Hsuang-Chang Chiang
口試委員: 連國龍
Kuo-Lung Lian
學位類別： 碩士
Master
系所名稱： 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年： 2014
畢業學年度： 102
語文別： 中文
論文頁數： 109
中文關鍵詞： 交流電源供應器 、變流器 、整流性負載 、模糊控制 、模糊類神經控制
外文關鍵詞： AC power supply, inverter, rectified load, fuzzy control, neural fuzzy control
相關次數： 點閱：229  下載：7 
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    • 使用交流電源供應器時，當內部的變流器遇上整流性的負載，會因為瞬間抽取過大的電流，使濾波器儲存的能量不足，因而導致電壓波形畸變，使得總諧波失真值提高，影響電源供應品質。
    在變流器的控制上，若要做到對負載的變動給予快速地因應，往往需要複雜的控制法則。而數位信號處理器不但可以引進此控制法則，而且不會有類比控制器受到元件劣化影響性能等優點。
    本研究藉由數位信號處理器(DSP TMS320F28335)，來引進以Psim軟體結合的模糊類神經網路控制法則，利用過去的誤差資訊，適當地修正標準正弦脈波分佈，進而解決濾波器儲能不足的問題，使變流器輸出電壓波形近似一正弦波形，經測試可降低總諧波失真至3%左右，進而有效地提升電源供應的效率及品質。

    If the internal inverter encounters rectified loads when an AC power supply is used, it will draw a large instantaneous current and will make filter storage energy inadequate, leading to a distorted voltage waveform so that the total harmonic distortion will be increased and the quality of the power supply is affected.
    To deliver a fast response to load in the converter control, it often requires complex control algorithms. A digital signal processor not only can adopt the control law, but also has the advantage of avoiding the effect of component degradation as an analog controller.
    This study uses a digital signal processor (DSP TMS320F28335). By adopting software Psim and combining the control law of neural fuzzy control, based on past error information, it can appropriately correct the sinusoidal waveforms and thereby solve the problem of inadequate energy storage for the filter. The inverter output voltage waveform, therefore, can be approximate to a sinusoidal waveform. Experiments results show that this method can reduce the total harmonic distortion to around 3%, which can effectively improve the efficiency and quality of the power supply.

    摘要…………………………………………………………………I Abstract………………………………………………………II 誌謝…………………………………………………………………III 目錄…………………………………………………………………IV 圖目錄………………………………………………………………VIII 表目錄………………………………………………………………XII 第一章 緒論…………………………………………………………1 1.1 研究背景與動機……………………………………………1 1.2 文獻回顧……………………………………………………4 1.3 研究目的……………………………………………………4 1.4 研究方法……………………………………………………5 1.5 章節概述……………………………………………………5 第二章 交流電源供應器簡介………………………………………7 2.1 前言…………………………………………………………7 2.2 EMI濾波器簡介……………………………………………8 2.3 功率因素修正器簡介……………………………………10 2.4 直流對直流轉換器簡介…………………………………14 第三章 變流器分析與設計………………………………………19 3.1 前言………………………………………………………19 3.2 單相橋式變流器架構及原理分析………………………19 3.3 脈波寬度調變控制原理…………………………………20 3.3.1 雙極性電壓切換……………………………………………20 3.3.2 單極性電壓切換……………………………………………21 3.4 系統架構及控制器設計……………………………………25 3.4.1 電路工作原理與模型推導…………………………25 3.4.2 控制器設計…………………………………………………27 3.5 變流器規格及輸出波型……………………………31 3.5.1 變流器規格…………………………………………31 3.5.2 Psim模擬電路及輸出波型………………………32 第四章 模糊類神經網路控制器設計……………………………37 4.1 前言………………………………………………………37 4.2 模糊控制…………………………………………………36 4.2.1 模糊控制簡介………………………………………36 4.2.2 模糊集合……………………………………………38 4.2.3 歸屬函數……………………………………………39 4.2.4 模糊規則及模糊推論………………………………42 4.2.5 解模糊化……………………………………………44 4.3 模糊類神經網路…………………………………………45 4.3.1 簡介…………………………………………………45 4.3.2 模糊類神經網路系統描述…………………………46 4.3.3 線上學習演算法則…………………………………49 4.4 模糊類神經網路控制器設計……………………………52 4.4.1 工具選用……………………………………………52 4.4.2 輸入端及輸出端定義………………………………53 4.4.3 參數設定……………………………………………57 4.4.4 整體控制迴路之實現……………………………59 4.4.5 暫態變化測試………………………………………60 第五章 實驗結果分析……………………………………………62 5.1 前言………………………………………………………62 5.2 實測步驟及TMS320F28335晶片功能介紹…………64 5.3 實驗結果…………………………………………………64 5.3.1 未加入模糊類神經網路控制器之變流器測試……64 5.3.2 加入模糊類神經網路控制器之變流器測試………67 第六章 結論與未來研究方向……………………………………74 6.1 結論………………………………………………………74 6.2 未來研究方向……………………………………………75 參考文獻………………………………………………………………76 附錄I 模糊類神經網路程式碼…………………………………81 附錄II 變流器硬體電路圖(主電路)…………………………91 附錄III 變流器硬體電路圖(Gate Driver)…………………………92 附錄IV 變流器硬體電路圖(Gate Driver Power)………………93

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