摘要
为实现数控机床可控励磁直线磁悬浮同步电动机(CELSM)进给系统的无速度传感器控制,需要准确获取电机速度和磁极位置的信息。提出一种利用电机电枢绕组电压和电流来估计CELSM速度和位置的方法,即基于H∞的扩展卡尔曼滤波算法。选择αβ坐标系下的电流iα、iβ、动子速度v和动子电角度θe作为状态变量,建立HEKF观测器的状态方程,并进行离散化。在扩展卡尔曼滤波基础上引入H∞滤波,设计一个滤波上界函数来限制估计误差的上界并最小化该上界,有效地提高了观测器对噪声的鲁棒性。仿真表明:在动态阶段,HEKF算法比EKF算法对速度和位置的估计更接近于实际值;当速度突变时,HEKF算法比EKF算法的鲁棒性更强。
In order to realize the speed sensorless control of the controllable excitation linear synchronous motor(CELSM)feed system of the CNC machine,it is necessary to accurately obtain the motor speed and magnetic pole position information.A method for estimating the speed and position of CELSM by using the armature winding voltage and current of the motor was proposed,namely the extended Kalman filtering algorithm based on H∞(HEKF).The current iα,iβ,the speed v and the electrical angleθe of the mover in theαβcoordinate system were selected as the state variables to establish the state equation of the HEKF observer,and the state equation was discretized.Based on extended Kalman filtering,a filtering upper bound function was designed to limit and minimize the upper bound of the estimation error,which effectively improves the robustness of the observer to the noise.The simulation shows that the speed and position estimation of the HEKF algorithm is closer to the actual value than the EKF algorithm in the dynamic phase;when the speed is abrupt,the robustness of HEKF algorithm is more robust than the EKF algorithm.
作者
蓝益鹏
任朝斌
LAN Yipeng;REN Chaobin(School of Electrical Engineering,Shenyang University of Technology,Shenyang Liaoning 110870,China)
出处
《机床与液压》
北大核心
2020年第15期93-96,102,共5页
Machine Tool & Hydraulics
基金
国家自然科学基金面上项目(51575363)。
关键词
数控机床
可控励磁
直线同步电动机
H∞
扩展卡尔曼滤波
CNC machine
Controllable excitation
Linear synchronous motor
H∞filtering
Extended Kalman filter
