引用本文:王孝洪,连维钊,翟名扬.基于改进型滑模观测器的永磁同步电机无位置传感器控制[J].控制理论与应用,2023,40(7):1243~1251.[点击复制]
WANG Xiao-hong,LIAN Wei-zhao,ZHAI Ming-yang.Sensorless control method of permanent magnet synchronous motor based on a modified sliding-mode observer[J].Control Theory and Technology,2023,40(7):1243~1251.[点击复制]
基于改进型滑模观测器的永磁同步电机无位置传感器控制
Sensorless control method of permanent magnet synchronous motor based on a modified sliding-mode observer
摘要点击 1200  全文点击 545  投稿时间：2022-05-29  修订日期：2023-06-15
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DOI编号  10.7641/CTA.2023.20460
  2023,40(7):1243-1251
中文关键词  永磁同步电机  滑模观测器  无位置传感器控制  自适应算法
英文关键词  permanent magnet synchronous motor  sliding-mode observer  sensorless control  adaptive algorithms
基金项目  国家自然科学基金项目(62173150), 珠海市产学研合作项目(ZH22017001210116PWC), 广东省基础与应用基础研究基金重点项目(2022B1515 120003)资助.
作者单位E-mail
王孝洪* 华南理工大学自动化科学与工程学院 xhwang@scut.edu.cn 
连维钊 华南理工大学自动化科学与工程学院  
翟名扬 华南理工大学自动化科学与工程学院  
中文摘要
      永磁同步电机无位置传感器控制技术通常使用滑模观测器观测反电动势, 进而获取转子位置和速度信息.为提升滑模观测器的性能, 本文设计了一种改进型自适应超螺旋滑模观测器. 首先, 文章在超螺旋滑模观测器结构中增加观测误差的线性项, 以提高观测器的动态性能. 接着, 为解决观测器增益在不同速域下参数不匹配的问题, 本文提出一种观测器参数自适应调整策略, 提升了观测器参数鲁棒性. 在此基础上, 采用同步参考系滤波器滤除输出信号的高次谐波, 进一步提高观测精度. 最后, 仿真结果表明, 与传统方法相比, 本文提出的方法观测性能更好, 鲁棒性更强.
英文摘要
      The sensorless control technology of permanent magnet synchronous motor usually uses sliding-mode observer to observe the back electromotive force, so as to obtain rotor position and speed information. In order to improve the performance of sliding-mode observer, a modified adaptive super-twisting sliding-mode observer is designed. Firstly, the linear term of observation error is added to the structure of super-twisting sliding-mode observer, in order to improve the dynamic performance of the observer. Then, to solve the problem of parameters mismatch of observer gain in different speed ranges, a self-adaptive adjustment strategy of observer gain parameters is proposed, and the robustness of observer parameters is improved. on this basis, the synchronous reference frame filter is used to filter out the high-order harmonics of the observed back electromotive force, and the observation accuracy is further enhanced. Finally, the simulation results show that the proposed method has better observation performance and stronger robustness than the traditional method.