基于无轨迹卡尔曼滤波器的感应电机转速估计被引量：8

Speed Estimation of Induction Machines Based on Unscented Kalman Filter

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摘要借助仿真,深入探讨了卡尔曼滤波器家族新成员—无轨迹卡尔曼滤波器(UKF)用于感应电机转速估计这一问题。分析了采样周期以及滤波器参数对UKF收敛特性的影响,从静态性能、动态响应速度、对电机参数的灵敏度、算法复杂度等各方面评价了UKF转速估计性能,并与经典的扩展卡尔曼滤波器(EKF)转速估计进行了比较。结果表明UKF并不能以预想的突出优势在感应电机转速估计问题上取代EKF。 With the aid of simulations, speed estimation of induction machines based on the new member of the Kalman filter family -- UnscentedKalman Filter （UKF） was discussed in depth. The effect of the sampling time and the parameters of the filter upon the speed estimation performances were analyzed, and the various aspects of the speed estimation performances of the UKF, such as stationary error, dynamic response speed, parameter sensitivities and algorithm complexity were evaluated. And the comparison between the UKF and the classical EKF was performed from every side. The simulation results show that the UKF can not replace the EKF with the expected outstanding advantages for the speed estimation of induction machines.

作者李洁钟彦儒

机构地区西安理工大学

出处《系统仿真学报》 EI CAS CSCD 北大核心 2006年第3期693-697,共5页 Journal of System Simulation

基金西安理工大学科技创新研究计划项目(105-210404)

关键词无轨迹卡尔曼滤波器感应电机转速估计无速度传感器控制 unscented Kalman filter induction machine speed estimation sensorless control

分类号 TM343 [电气工程—电机] TN953 [电子电信—信号与信息处理]

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