微特电机 ›› 2023, Vol. 51 ›› Issue (4): 52-56.

• 驱动控制 • 上一篇    下一篇

基于测量噪声方差自适应的EKF无传感器控制

张雨, 刘宁, 王迎发   

  1. 中国电子科技集团公司第五十四研究所,石家庄 050050
  • 收稿日期:2023-01-16 出版日期:2023-04-28 发布日期:2023-04-25
  • 作者简介:张雨(1988—),男,博士,工程师,研究方向为电机控制及功率变换技术。

Sensorless Control of EKF Based on Adaptive Measurement Noise Variance

ZHANG Yu, LIU Ning, WANG Yingfa   

  1. China Electronics Technology Group Corporation 54th Research Institute, Shijiazhuang 050050, China
  • Received:2023-01-16 Online:2023-04-28 Published:2023-04-25

摘要: 提出一种测量噪声方差自适应的扩展卡尔曼滤波(EKF)算法。该算法分别对当前时刻和前一时刻的观测值施加两次EKF算法,将速度与位置观测值的误差百分比的加权和作为测量噪声方差的加权系数,实现测量噪声方差的自适应调整,提高转速和位置的观测精度和控制性能。通过实验平台验证了该算法的可行性。

关键词: 永磁同步电机, 无传感器控制, 自适应算法, 扩展卡尔曼滤波

Abstract: An adaptive noise variance extended Kalman filter(EKF) algorithm was proposed. The algorithm applied the EKF algorithm twice to the observations at the current time and the previous time respectively, and took the weighted sum of the error percentage of the motor speed and position observations as the weighting coefficient of the measurement noise variance. The adaptive adjustment of measurement noise variance was realized, and the observation accuracy and control performance of motor speed and position were improved.The feasibility of the proposed algorithm was verified by an experimental platform.

Key words: permanent magnet synchronous motor(PMSM), sensorless control, adaptive algorithm, extended Kalman filter(EKF)

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