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Sensorless permanent magnet synchronous motor drive using an optimized and normalized Extended Kalman filter

  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

In this paper, normalised state vectors are used to demonstrate the state equations of Extended Kalman Filter (EKF) based sensorless Permanent Magnet Synchronous Motor (PMSM) drive. Based on the normalised EKF equations, Simple Genetic Algorithm (SGA) is employed to optimize the noise covariance and weight matrices of EKF parameters, which thereby reduces the parameter adjusting time and ensures stability of filters in estimations of position and speed. The simulations for SGA training are carried out by MATLAB/Simulink. The experimental sensorless drive system employing Field Oriented Control (FOC) method and SGA is implemented on STM32F103. The simulating and experimental results indicate the effectiveness of the proposed method.

源语言英语
主期刊名2011 International Conference on Electrical Machines and Systems, ICEMS 2011
DOI
出版状态已出版 - 2011
活动2011 International Conference on Electrical Machines and Systems, ICEMS 2011 - Beijing, 中国
期限: 20 8月 201123 8月 2011

出版系列

姓名2011 International Conference on Electrical Machines and Systems, ICEMS 2011

会议

会议2011 International Conference on Electrical Machines and Systems, ICEMS 2011
国家/地区中国
Beijing
时期20/08/1123/08/11

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