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研究生:洪瑞志
研究生(外文):HONG,RUEI-JHIH
論文名稱:基於類神經網路相鎖迴速度觀測器之永磁同步馬達無感測控制
論文名稱(外文):Sensorless Control Based Neural Network Phase-Locked Loop Velocity Observer for Permanent Magnet Synchronous Motor
指導教授:王明賢王明賢引用關係
指導教授(外文):WANG, MING-SHYAN
口試委員:謝旻甫白能勝
口試委員(外文):HSIEH, MIN-FUPAI, NENG-SHENG
口試日期:2017-07-04
學位類別:碩士
校院名稱:南臺科技大學
系所名稱:電機工程系
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:2017
畢業學年度:105
語文別:中文
論文頁數:87
中文關鍵詞:永磁同步馬達類神經控制無感測器控制速度觀測器
外文關鍵詞:Permanent magnet synchronous motorneural network controlsensorless controlvelocity observer
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馬達控制領域上,使用位置感測器來得知位置資訊以及轉速,來達到馬達控制轉速和定位。但在某些嚴苛的場合上,位置感測器會因受到外部干擾而誤動作以及成本上的考量,因此本論文提出在不使用位置感測器的情形下,進行位置以及轉速估測來達到馬達控制。
本論文針對以低時間消耗和低成本,設計無感測控制(Sensorless Control)類神經速度觀測器估測角度及速度,使用在表面貼磁永磁同步馬達(Surface Permanent Magnet Synchronous Motor)控制上。此無感測控制主要是不使用電壓感測器,而是藉電流控制器回授計算出參考電壓從而得知反電動勢,得到的反電動勢後即可以估測出角度,再由轉子位置來進行馬達運轉速度的估測。然而這個方法在馬達運轉過程中,會因為電流資訊運算以及整流電路形成的相位落後,導致位置估測的誤差使控制的系統不穩定甚至馬達運轉失敗。本論文將使用類神經控制結合閉迴相鎖迴路(Phase Locked Loop, PLL)來增加估測角度的準確性,以達到系統的穩定及強健性。而類神經網路參數更新是基於最陡坡降法(Gradient Descent Method),求得類神經網路權重值之最佳解,並以實驗來驗證無感測控制的結果以證實系統的優劣。
本論文使用微芯片科技公司之dsPIC30F6010A數位訊號單晶片,運用其高速ADC模組回授電流資訊進而估測轉子位置,並利用磁場導向控制(Field Oriented Control, FOC)來實現馬達之電流控制和無感測器速度控制。

The motor control field, the use of position sensors to know the location information and speed, to achieve the motor control speed and positioning. However, in some harsh conditions, the position sensor will be due to external interference and malfunction and cost considerations, so this paper does not use the position sensor in the case of the location and speed estimation to achieve motor control.
In this thesis, we aim at estimating the angle and velocity control of the sensorless neural velocity observer with low time consumption and low cost. For the surface permanent magnet synchronous motor (SPMSM), this sensorless control does not use the voltage sensor, but by the current feedback to calculate the reference voltage to deduce the back electromotive force, which can be used to estimate the rotor angle, and then the motor speed. However, during the motor running process, this method will result in the error of the rotor position due to the current information calculation and the rectifier circuit phase lag, even the instability. In this thesis, we will use the neural networks combined with the closed-loop phase-locked loop (PLL) to increase the accuracy of the estimation angle to achieve the stability and robustness of the system. The updating of neural network parameters is based on the steepest descent method to find the best solutions of weightings. The experiments will verify the results of sensorless control and confirm the merits of the system.
In this thesis, the dsPIC30F6010A digital signal single chip of Microchip Technology Company is used to estimate the rotor position by using the high-speed ADC module. The current control and sensorless speed control of the motor is realized by Field Oriented Control (FOC).

目 次
摘 要 I
Abstract II
誌謝 III
目 次 IV
目 次 V
圖目錄 VI
圖目錄 VII
圖目錄 VIII
表目錄 IX
第一章 緒論 1
  1.1 前言 1
1.2 文獻回顧 2
  1.3 內容大綱 4
第二章 數位訊號周邊介面控制器 5
   2.1 dsPIC30F系列微控制器 5
2.2周邊功能應用設定 6
2.2.1 Timer計時/計數器 6
2.2.2 Interrupt中斷功能單元 6
2.2.3脈波寬度調變技術(Pulse Width Modulation) 6
2.2.4高速類比數位訊號轉換器(ADC)模組 8
第三章 永磁同步馬達模式化簡介 9
  3.1 永磁同步馬達之數學模型 9
  3.2 座標轉換 10
  3.3 d-q座標表示之電路方程式 13
3.4 電動機之轉矩 14
第四章 空間向量脈波寬度調變(SVPWM) 15
  4.1空間向量設計 15
  4.2 SVPWM之推導 16
第五章 無感測器控制設計 24
  5.1反電動勢轉子角度估測理論 25
5.2反電動勢估測法 26
5.3速度觀測器估測法 29
第六章 類神經網路控制器推論與探討 32
  6.1類神經網路系統設計 32
6.1.1類神經網路系統架構 32
6.1.2倒傳遞演算法 33
6.2類神經控制器設計 34
6.3多層感知器架構 35
6.3.1線上參數學習演算法 38
第七章 系統架構與實驗結果 41
  7.1系統架構 41
7.2實驗平台介紹 41
7.3實驗結果 44
7.3.1無感測角度估測 44
7.3.2空載速度響應實驗 57
7.3.3加載速度響應實驗 66
第八章 結論與未來展望 71
  8.1結論 71
8.2未來展望 71
參考文獻 72

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