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Gradient descent based optimization for position and speed estimation of permanent magnet synchronous motor at low speed

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2 Author(s)
Khan, A.A. ; Dept. of Electr. & Comput. Eng., Florida Int. Univ., Miami, FL, USA ; Mohammed, O.A.

The optimization of low speed sensorless algorithm parameters is considered to be difficult due to large number of parameters involved. In this paper, a gradient descent based optimization is proposed to optimize the parameters of low speed sensorless algorithm to improve speed and position estimation performance. The finite element based phase variable model of permanent magnet synchronous motor is used for simulation of low speed sensorless algorithm. The proposed optimization method improves both dynamic and steady state response characteristic of estimated position and estimated speed.

Published in:

Power & Energy Society General Meeting, 2009. PES '09. IEEE

Date of Conference:

26-30 July 2009