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  • 學位論文

以遞迴式模糊類神經網路控制器為基礎之無量測器感應主軸馬達高頻驅動系統

Speed Sensorless Induction Spindle Motor Based on Recurrent Fuzzy Neural Network Controller

指導教授 : 林法正
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摘要


本論文主要目的在發展三相感應主軸馬達(Induction Spindle Motor)之高頻驅動系統,並發展配合此高頻驅動系統之馬達轉速估測及轉速控制法則。本論文首先發展新型之1KHz同步脈波寬度調變(Pulse Width Modulation, PWM)技術以降低高頻反流器(Inverter)之輸出電壓及電流諧波,並利用FPGA設計延遲時間補償(Dead-Time Compensation)技術以提高電壓利用率,並利用IGBT元件實現高頻反流器。在驅動系統之控制上,本論文採用個人電腦(PC)對感應主軸馬達驅動系統做電壓/頻率( )等比例控制。在另一方面,由於一般高速感應主軸馬達在數萬轉之使用情況下均無法加裝轉速計,造成馬達之轉速及動態特性無法控制,因此本論文亦發展感應主軸馬達之無量測轉速觀測器,並利用遞迴式模糊類神經網路發展感應主軸馬達之速度控制器。本文除敘述上述控制器完整的理論基礎外,並利用模擬與實驗結果驗證所提出之三相感應主軸馬達驅動系統的有效性與實用性。

並列摘要


The purpose of this thesis is to develop a high frequency drive system with advanced rotor speed estimation and control algorithms for the three-phase induction spindle motor. First, a new type synchronous pulse width modulation (PWM) techniques with 1KHz switching frequency is developed to reduce the harmonic components of the output voltages and currents of the high-frequency inverter. Moreover, the dead-time compensation technique using FPGA is developed to increase the voltage utilization of the inverter. The high-frequency inverter is implemented using IGBT switching components. Then a personal computer (PC) is adopted to control the motor drive system with voltage/frequency ( ) constant control. On the other hand, since the tachometer and encoder are impossible to couple to the rotor of the spindle motor for rotor speed higher than few ten thousands rpm, the rotor speed and dynamic can not be controlled precisely. Therefore, the development of advanced rotor speed estimator is necessary. Furthermore, the speed controller is developed using recurrent fuzzy neural network (RFNN). The theoretical basis of the proposed estimator and controller are derived in detail, and the effectiveness of the proposed spindle motor drive system is confirmed by simulation and experimental results.

參考文獻


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