微特电机 ›› 2018, Vol. 46 ›› Issue (12): 54-57.doi: 1004-7018(2018)12-0054-04

• 驱动控制 • 上一篇    下一篇

结合稳态卡尔曼滤波的永磁同步电机滑模观测器

莫丽琴   

  1. 江苏海事职业技术学院, 南京 211170
  • 收稿日期:2017-04-18 出版日期:2018-12-28 发布日期:2018-12-28
  • 作者简介:莫丽琴(1978—)女,硕士,讲师,研究方向为电气自动化。

Sliding Model Observer for Permanent Magnet Synchronous Motor Combined with Steady-State Extended Kalman Filter

MO Li-qin   

  1. Jiangsu Maritime Institute,Nanjing 211170,China
  • Received:2017-04-18 Online:2018-12-28 Published:2018-12-28

摘要:

采用滑模观测器进行永磁同步电机的转子位置和转速估计,实现了永磁同步电机的无传感器控制。研究了一种改进的滑模观测器,在传统滑模的基础上加入稳态卡尔曼滤波器,能够快速、有效地减弱抖振。相比于传统的锁相环滤波,稳态卡尔曼滤波器能够获得更高的精度和更快的响应速度,且由于其增益矩阵固定为常数,因此计算量很小。仿真和实验结果表明,结合了稳态卡尔曼滤波的滑模观测器能够获得更干净的反电动势信息,最终的位置观测误差更小。

关键词: 永磁同步电机, 无传感器控制, 滑模观测器, 稳态卡尔曼滤波

Abstract:

Sliding model observer (SMO) was adopted to estimate the rotor position and rotor speed of permanent magnetic synchronous motor (PMSM) so as to achieve its sensorless control. An improved SMO was presented, and steady-state extended Kalman filter (SSEKF) was plugged into the SMO,so that the chattering can be diminished quickly and effectively.Compared with the conventional filter of phase-loop lock, SSEKF can achieve higher accuracy and faster response.As the Kalman gain matrix is set as constant, SSEKF is not time-consuming.Simulation and experimental results show SMO combined with SSEKF can obtain cleaner back-EMF, and the position error is smaller.

Key words: permanent magnet synchronous motor (PMSM), sensorless control, sliding model observer (SMO), steady-state extended Kalman filter (SSEKF)

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