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无轴承永磁同步电机无速度传感器控制系统
引用本文:朱熀秋,陈朝亮,邓建明,成秋良.无轴承永磁同步电机无速度传感器控制系统[J].电机与控制应用,2008,35(5):18-22.
作者姓名:朱熀秋  陈朝亮  邓建明  成秋良
作者单位:江苏大学,电气信息工程学院,江苏,镇江,212013
基金项目:国家自然科学基金 , 国家高技术研究发展计划(863计划)
摘    要:基于无轴承永磁同步电机的矢量控制系统,提出了采用扩展卡尔曼滤波器实现无速度传感器运行的控制策略。通过测量电机的端电压和流过定子线圈的电流在线估计电机转子的速度,实现具有较强自适应和抗干扰能力的无轴承永磁同步电机无传感器调速系统。建立了无轴承永磁同步电机状态方程及扩展卡尔曼滤波器速度估计离散算法。在MATLAB/Simulink环境下构建了无速度传感器运行仿真系统,对速度的辨识、电机的动态特性进行了仿真。仿真结果表明:扩展卡尔曼滤波器的速度辨识精度较高,具有良好的鲁棒性,基本满足无轴承电机无传感运行的要求。

关 键 词:无轴承永磁同步电机  扩展卡尔曼滤波器  无速度传感器  仿真
文章编号:1673-6540(2008)05-0018-05
修稿时间:2007年8月24日

Research on Speed-Sensorless Control System of Bearingless Permanent Magnet Synchronous Motor
ZHU Huang-qiu,CHEN Zhao-liang,DENG Jian-ming,CHENG Qiu-liang.Research on Speed-Sensorless Control System of Bearingless Permanent Magnet Synchronous Motor[J].Electric Machines & Control Application,2008,35(5):18-22.
Authors:ZHU Huang-qiu  CHEN Zhao-liang  DENG Jian-ming  CHENG Qiu-liang
Abstract:Based on vector control system of Bearingless Permanent Magnet Synchronous Motor(BPMSM),a speed-sensorless control strategy using Extended Kalman Filter(EKF) was presented.By the survey on the motor of the terminal voltage and the electric current passing the coil of stator,the motor rotor speed could be estimated online,the strong adaptive and anti-interference BPMSM sensorless vector control system was realized.State equations of the BPMSM and speed estimation discrete arithmetic based on EKF were established.Simulation system of speed-sensorless running in MATLAB/Simulink simulation environment was developed and simulations of speed identification and dynamic characteristics of motors were carried out.The simulation results had shown that the EKF speed identification precision was very good,and the method had a strong robustness,and sensorless operation demands of the BPMSM were basically satisfied.
Keywords:bearingless permanent magnet synchronous motor  extended kalman filter  speed-sensorless  simulation
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