摘要
采用扩展卡尔曼滤波(EKF)的永磁同步电机无传感器控制在系统运行环境改变时不能适应系统参数的变化,可能会出现滤波发散的情况。针对EKF的问题,已有不少的改进方法,但多需要大幅增加算法的复杂度。研究了一种算法简洁的自适应扩展卡尔曼滤波方法(AEKF)。通过仿真实验验证了该AEKF方法的稳态收敛精度和对参数的鲁棒性均优于传统的EKF方法。
The sensorless control method of permanent magnet synchronous motor using extended Kalman filter(EKF)cannot adapt to the changes of system parameters when the system operating environment changes.The filtering divergence may occur.There are many improved methods for this problem of EKF,but most of them need to greatly increase the complexity of the algorithm.An adaptive extended Kalman filter(AEKF)with simple algorithm was studied.The simulation results show that the AEKF algorithm is superior to the traditional EKF algorithm in terms of steady convergence accuracy and parameters robustness.
作者
孙浩
沈艳霞
SUN Hao;SHEN Yanxia(School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China)
出处
《微特电机》
2023年第3期48-53,共6页
Small & Special Electrical Machines
关键词
永磁同步电机
转速估计
无传感器控制
自适应卡尔曼滤波
permanent magnet synchronous motor(PMSM)
speed estimation
sensorless control
adaptive extended Kalman filter(AEKF)
