基于扩展卡尔曼滤波辨识永磁同步直线伺服系统的负载惯量参数

Identification of Load Inertia Parameters in Permanent Magnet Synchronous Linear Servo Systems Using Extended Kalman Filtering

针对目前永磁同步直线电机带柔性负载产生谐振频率的辨识问题,提出通过使用非线性扩展卡尔曼滤波器(EKF)辨识负载惯量进行对谐振频率的计算。首先建立电机-柔性连接-负载的二质量系统模型;其次在系统模型上搭建EKF算法,重点研究EKF算法在二质量系统模型中状态方程与量测方程的建立。建立EKF二质量系统仿真模型,并进行仿真实验;最后将EKF算法应用在永磁同步直线电机系统之中进行辨识,实现对永磁同步直线电机带柔性负载的负载惯量辨识,根据仿真验证能在0.1 s以内辨识0.1 kg*m 2负载惯量。在惯量变换时能够实时修正辨识结果,辨识误差小于1%。

Addressing the issue of resonance frequency identification in permanent magnet synchronous linear motors with flexible loads,this paper proposes the calculation of the resonance frequency by employing a nonlinear Extended Kalman Filter(EKF)for load inertia identification.This study initially establishes a dual-mass system model,then implements the EKF algorithm on the system model,with a focus on formulating the state and measurement equations within the dual-mass system model.An EKF dual-mass system simulation model is developed,and simulation experiments are conducted.Finally,the EKF algorithm is applied to the permanent magnet synchronous linear motor system for identification,achieving load inertia identification for permanent magnet synchronous linear motors with flexible loads.Simulation validation demonstrates the capability to identify a 0.1 kg*m 2 load inertia within 0.1 seconds.During inertia transformation,the identification results can be promptly corrected in real-time,with an identification error of less than 1%.