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研究生:高子胤
研究生(外文):Zi-Yin Kao
論文名稱:以反電動勢為基礎之比例積分微分類神經網路估測器之無感測器變頻壓縮機驅動系統開發
論文名稱(外文):Development of sensorless inverter-fed compressor drive system using back EMF based proportional-integral-derivative neural network estimator
指導教授:林法正林法正引用關係
指導教授(外文):Faa-Jeng Lin
學位類別:碩士
校院名稱:國立中央大學
系所名稱:電機工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:143
中文關鍵詞:高頻方波電壓注入法以反電動勢為基礎之速度估測法永磁同步馬達比例積分微分類神經網路無感測變頻壓縮機
外文關鍵詞:sensorless inverter-fed compressorpermanent ma
相關次數:
  • 被引用被引用:15
  • 點閱點閱:278
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本論文提出一個利用比例積分微分類神經網路估測器之以凸極式反電動勢為基礎之速度估測法,以改善內藏式永磁同步馬達應用在變頻壓縮機驅動系統之估測性能。此外本論文將提出兩種無感測技術,其一為高頻方波電壓注入法結合利用比例積分微分估測器之以凸極式反電動勢為基礎之速度估測法,其二為高頻方波電壓注入法結合利用比例積分微分類神經網路估測器之以凸極式反電動勢為基礎之速度估測法。以上兩種無感測控制機制皆是使用高頻方波電壓注入法作為馬達之啟動策略,以達成弦波啟動之目的。當馬達逐漸加速至預設的轉速時,系統會切換到利用比例積分微分估測器之以凸極式反電動勢為基礎之速度估測法或利用比例積分微分類神經網路估測器之以凸極式反電動勢為基礎之速度估測法。本文將詳細的分析高頻方波電壓注入法、利用比例積分微分估測之以凸極式反電動勢為基礎之速度估測法。此外,比例積分微分類神經網路的網路架構、線上學習法則、以及收斂性分析將在本文被詳細的討論。最後將以DSP實現變頻壓縮機驅動系統,並且以實驗結果驗證所提出方法之可行性。
A saliency back EMF based proportional-integral-derivative neural network (PIDNN) estimator is proposed in this study to improve the speed estimating performance of the interior permanent magnet synchronous motor (IPMSM) used in inverter-fed compressor drive systems. Two sensorless control schemes are designed for the IPMSM drive system. One is the square wave type voltage injection method combined with the conventional saliency back EMF based speed estimation method using PID estimator, and the other is the square wave type voltage injection method combined with the saliency back EMF based speed estimation method using PIDNN estimator. Both sensorless control schemes use square wave type voltage injection method as the start-up strategy to achieve sinusoidal starting. When the motor speed gradually increases to a preset speed, the sensorless drive will switch to the conventional saliency back EMF based speed estimation method using PID estimator or the saliency back EMF based speed estimation method using PIDNN estimator for medium and high speed control. The theories of the square wave type voltage injection method and the conventional saliency back EMF based speed estimation method are introduced. Moreover, the network structure, the online learning algorithms and the convergence analyses of the PIDNN are discussed in detail. Furthermore, a DSP-based control system is developed to implement the sensorless inverter-fed compressor drive system. Finally, some experimental results are given to verify the feasibility of the proposed control schemes.
中文摘要 I
英文摘要 II
致謝 III
目錄 IV
圖目錄 VII
表目錄 XIII

第一章 緒論 1
第二章 空調系統介紹 10
第三章 變頻驅動器硬體介紹 27
第四章 內藏式永磁同步馬達數學模型介紹 43
第五章 高頻方波電壓注入法 63
第六章 利用比例積分微分估測器之以凸極式反電動勢為基礎之
速度估測法 71
第七章 利用比例積分微分類神經網路估測器之以凸極式反電動
勢為基礎之速度估測法 80
第八章 模擬結果 88
第九章 實驗結果 109
第十章 結論與未來研究方向 135

參考文獻 137
作者簡歷 142
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