Rotor Displacement Estimation for MB Sensorless Control

• Autorzy: Zhu Z. , Sun Y. , Huang Y. , Ji X.

Warianty tytułu

PL

Estymacja położenia wirnika w maszynach z poduszką magnetyczną

• Języki publikacji: EN

Abstrakty

EN

This paper presents an on-line recursive least squares support vector machine(O-RLS-SVM)-based displacement estimator for magnetic bearings (MBs). The basic premise of the method is that an O-RLS-SVM forms an efficient mapping structure for a nonlinear MB. Through the measurement of phase flux linkages and currents, the O-RLS-SVM is able to estimate the rotor displacement; thereby it facilitates the elimination of the rotor displacement sensor. Simulation results show that the estimator has high estimation precision and favourable operation efficiency.

PL

W artykule przedstawiono system estymacji położenia wirniku w maszynach z poduszką magnetyczną. System nie wymaga czujników – miarą położenia wirnika są przesunięcia fazowe prądu i strumienia magnetycznego.

Słowa kluczowe

EN

active magnetic bearing; least squares support vector machine; displacement estimation; sensorless control

PL

aktywne unoszenie magnetyczne; maszyny elektryczne; wirnik

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 1b
• Strony: 141--145
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Zhu Z.

autor

Sun Y.

autor

Huang Y.

autor

Ji X.

• School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013 China,

Bibliografia

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• [2] Daniel Martsa, Miklos Kuczmann, Optimization and Finite Element Analysis of 3-Pole Magnetic Bearing with Nonlinear Material, Przeglad Elektrotechniczny, 86(2010) No.12, 91-94.
• [3] Albritton N. G., and Hung J. Y., Observers for Sensorless Control of Industrial Magnetic Bearings, International Conference on Industrial Electronics, Control, and Instrumentation, 2 (1995), 973-978.
• [4] Matsuda K., Kijimoto S., and Kanemitsu Y., Self-sensing Three- Pole Magnetic Bearing Using A Kalman Filter, SICE-ICASE International Joint Conference, (2006), 1590-1594.
• [5] Mese E., Torrey D. A., An Approach for Sensorless Position Estimation for Switched Reluctance Motors Using Artifical Neural Networks, IEEE Transactions on Power Electronics, 17(2002), No. 1, 66-75.
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• [7] Suykens J. A. K., and Vandewalle J., Recurrent Least Squares Support Vector Machines, IEEE Transactions on Circuits and Systems I, 47(2000), No. 7, 1109-1114.
• [8] Suykens J. A. K., Support Vector Machines: A Nonlinear Modeling and Control Perspective. European Journal of Control, 7(2001),311-327.
• [9] Sun Yukun, Zhu Zhiying. Inverse-Model Identification and Decoupling Control Based on Least Squares Support Vector Machine for 3 Degree-of-Freedom Hybrid Magnetic Bearing, Proceedings of the Chinese Society of Electrical Engineering, 30(2010), No. 15, 112-117.
• [10] Ji Shanghua, Zhang Weiyu, Huang Zhenyue, Zhu Huangqiu, Parameter design and optimization of AC active magnetic bearing, Proceedings of the Chinese Society of Electrical Engineering, 31(2011), No.21, 150-157.
• [11] Huang Zhenyue, Zou Haidan, Zhu Huangqiu, Li Tianbo, Simulation of Self-sensing Technique for 3-phase AC Active Magnetic Bearings, Proceedings of the Chinese Society of Electrical Engineering, (2009), No.S1, 228-233.
• [12] Shyh-Leh Chen,Cheng-Chi Weng, Robust Control of a Voltage- Controlled Three-Pole Active Magnetic Bearing System, IEEE/ ASME Transactions on Mechatronics, 15(2010), No.3, 381-388.