在线建模的开关磁阻电机四象限运行无位置传感器控制

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Abstract A position sensorless control method based on on-line modeling is presented for switched reluctance motors(SRM). Radial basis function(RBF) neural network of rotor position estimation for sensorless SRM control is established with two input variables: flux linkage and phase current. Real-time rotor position angle obtained from shaft encoder is adopted as learning sample data, and on-line modeling of SRM is realized. Excitation pulse method combined with sliding mode observer(SMO) strategy is proposed and four-quadrant SRM sensorless operation is achieved. Experimental results indicate that rotor position estimation error less than 2° and switching between quadrants is reliable, and the system has good dynamic and static performance. The proposed method is helpful for high-power sensorless control of SRM.

Key words： Switched reluctance motor on-line modeling neural network sensorless four-quadrant

Received: 21 March 2011 Published: 20 March 2014

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TM352

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	Zhang Xulong
	Tan Guojun
	Kuai Songyan
	Liu Songyong
	Wang Qihu

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Zhang Xulong,Tan Guojun,Kuai Songyan等. Four-Quadrant Position Sensorless Control of Switched Reluctance Motors Based on On-Line Modeling[J]. Transactions of China Electrotechnical Society, 2012, 27(7): 26-33.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2012/V27/I7/26

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