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研究生: 賴昶典
Chang-Tien Lai
論文名稱: 以擴展型卡爾曼濾波器為基礎之感應馬達無感測器控制
EKF-based Speed-sensorless Control of Induction Motor
指導教授: 姜嘉瑞
Chia-Jui Chiang
口試委員: 黃仲欽
劉添華
學位類別: 碩士
Master
系所名稱: 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年: 2018
畢業學年度: 106
語文別: 中文
論文頁數: 152
中文關鍵詞: 感應馬達擴展型卡爾曼濾波器無速度感測器控制
外文關鍵詞: induction motor, EKF, speed-sensorless control
相關次數: 點閱:320下載:1
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交流馬達因向量控制的蓬勃發展而成為工業界的主流,其中感應馬達更因為
堅固、耐用等優點有著廣泛的應用,而無感測控制的以估測器省去了轉軸角度
及轉速感測器的成本且增加了可能的應用範圍。以擴展型卡爾曼濾波器(Extend
Kalman Filter, EKF) 為基礎所發展之估測器因具有雜訊免疫及線上即時估測的能
力,使其在無感測控制議題上廣泛的被採用,本論文以EKF 進行狀態的估測,並
且透過轉子磁場導向控制(FOC) 實現無速度感測控制。
實驗的結果顯示,轉子磁場導向的控制效能良好,在設計的兩個操作條件下均
可以維持最大穩態誤差小於0.1% 及方均根誤差6 rpm 以內;估測器的參數收斂時
間在1.5 秒內,轉速穩態誤差也在2% 內。結合兩者的無感測控制在操作條件下最
大穩態誤差皆在1.5% 內,方均根誤差亦小於30 rpm 。由於估測器延遲及控制器
最大超越量,對轉速變化的估測及控制效能較差。


AC motor have become popular in the industries globally due to the booming of vector
control. Among them, induction motors(IM) have a wide range of applications because of
its sturdiness and durability. To reduce the expenses and to open more possibilities on its
application speed-sensorless control is preferred. However, in applying speed-sensorless
control efficiently an observer is needed. The noise immunity and real time estimation
ability of Extended Kalman filter(EKF)-based observer lead to a popular application in
field of speed-sensorless control. This thesis utilize EKF based estimator and FOC as
the controller in order to completed the speed-sensorless control. The experimental results
show that the FOC has good control performance, and can maintain the zero steady
error and the RMSE within 6 rpm under the designed operating conditions of constant
speed variable loading and variable speed constant loading. The convergence efficiency
of the estimator is acceptable. The convergence time of speed and load in 1.5 seconds,
the Maximum of the steady state error is also less than 0.1%. The control performance of
EKF-based speed-sensorless control works well. The Maximum of steady state error of
the speed is less than 1.5% and the RMSE within 30 rpm. Due to the estimator delay and
the maximum overshoot of the controller, the estimation of the rotational speed change
and the control performance are not so well.

第一章 緒論 第二章 實驗系統架構 第三章 感應馬達模型建立 第四章 控制器及估測器設計 第五章 實驗及模擬結果 第六章 結論與未來展望

黃仲欽, 「電機機械理論」 . 課程講義, 2015.
N. G. Bilal Akin, 「 Scalar (V/f) Control of 3-Phase Induction Motors 」 . Texas
Instruments, Inc., 2013.
de:Benutzer:Kku . (2003) [Online]. Available:https://commons.wikimedia.org/wiki/
File:Hmm.png.
Ciphergoth. (2006) [Online]. Available:https:// commons.wikimedia.org/ wiki/
File:Kalman filter model.png.
謝仲翔, 「空間向量??調變驅控之鼠籠式感應馬達動態建模」 . 國立台灣科技大學機械工程學系,碩士論文, 2017.
劉昌煥, 「交流電機控制 - 向量控制與直接轉矩控制原理」 . 東華書局, 2008.
王衍凱, 「以擴展型卡爾曼濾波器為基礎之感應馬達無感測器控制及定子與轉子阻抗估測」 . 國立台灣科技大學機械工程學系,碩士論文, 2010.
S. Das, A. Pal, R. Kumar, and A. K. Chattopadhyay, “An improved rotor flux based
model reference adaptive controller for four-quadrant vector controlled induction
motor drives,” in TENCON 2015 - 2015 IEEE Region 10 Conference, pp. 1–6.
Y. Bensalem and M. N. Abdelkrim, “A sensorless neural model reference adaptive
controlforinductionmotordrives,”in20093rdInternationalConferenceonSignals,
Circuits and Systems (SCS), pp. 1–6.
S. Maiti, C. Chakraborty, Y. Hori, and M. C. Ta, “Model reference adaptive
controller-based rotor resistance and speed estimation techniques for vector con-
trolled induction motor drive utilizing reactive power,” IEEE Transactions on In-
dustrial Electronics, vol. 55, no. 2, pp. 594–601, 2008.
R. Verma, V. Verma, and C. Chakraborty, “Ann based sensorless vector controlled
induction motor drive suitable for four quadrant operation,” in Students’ Technology
Symposium (TechSym), 2014 IEEE, pp. 182–187.
S. T. Nguyen, P. H. Pham, T. V. Pham, H. X. Ha, C. T. Nguyen, and P. C. Do, “A
sensorlessthree-phaseinductionmotordriveusingindirectfieldorientedcontroland
artificial neural network,” in 2017 12th IEEE Conference on Industrial Electronics
and Applications (ICIEA), pp. 1454–1459.
M. Barut, S. Bogosyan, and M. Gokasan, “Experimental evaluation of braided ekf
for sensorless control of induction motors,” IEEE Transactions on Industrial Electronics, vol. 55, no. 2, pp. 620–632, 2008.
Z. Yin, G. Li, Y. Zhang, J. Liu, X. Sun, and Y. Zhong, “A speed and flux observer of induction motor based on extended kalman filter and markov chain,” IEEE Transactions on Power Electronics, vol. 32, no. 9, pp. 7096–7117, 2017.
K.V.Shivaramakrishna, A.K.Chauhan, M.Raghuram, andS.K.Singh, “Sensorless
control of induction motor using ekf: Analysis of parameter variation on ekf performance,” in 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), pp. 1–4.
Y. Zahraoui, C. Fahassa, M. Akherraz, and A. Bennassar, “Sensorless vector control of induction motor using an ekf and svpwm algorithm,” in 2016 5th International Conference on Multimedia Computing and Systems (ICMCS), pp. 588–593.
M. Khafallah, A. E. Afia, A. Cheriti, F. E. Mariami, A. Saad, and B. E. Moussaoui, “Ekf based speed sensorless vector control of an induction machine,” in Industrial Technology, 2004. IEEE ICIT ’04. 2004 IEEE International Conference on, vol. 3, pp. 1338–1344 Vol. 3.
K. Ogata, Discrete time control systems. Prentice Hall, Inc., 1987.
K. L. Shi, T. F. Chan, Y. K. Wong, and S. L. Ho, “Speed estimation of an induc-
tion motor drive using an optimized extended kalman filter,” IEEE Transactions on
Industrial Electronics, vol. 49, no. 1, pp. 124–133, 2002.

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