博碩士論文 985201007 完整後設資料紀錄

DC 欄位 語言
DC.contributor電機工程學系zh_TW
DC.creator高子胤zh_TW
DC.creatorZi-Yin Kaoen_US
dc.date.accessioned2011-8-18T07:39:07Z
dc.date.available2011-8-18T07:39:07Z
dc.date.issued2011
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=985201007
dc.contributor.department電機工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract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。 zh_TW
dc.description.abstractA 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. en_US
DC.subject高頻方波電壓注入法zh_TW
DC.subject以反電動勢為基礎之速度估測法zh_TW
DC.subject永磁同步馬達zh_TW
DC.subject比例積分微分類神經網路zh_TW
DC.subject無感測變頻壓縮機zh_TW
DC.subjectsensorless inverter-fed compressoren_US
DC.subjectpermanent maen_US
DC.title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zh_TW
dc.language.isozh-TWzh-TW
DC.titleDevelopment of sensorless inverter-fed compressor drive system using back EMF based proportional-integral-derivative neural network estimatoren_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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