基于优化新EKF的直线感应电动机速度估计  

Speed Estimation of Linear Induction Motor Using a Novel Optimized Extended Kalman Filter

作　　者：冯尚明[1] 杨波[1] 

机构地区：[1]北京航空航天大学,北京100191

出　　处：《微特电机》2009年第7期20-23,66,共5页Small & Special Electrical Machines

基　　金：教育部留学人员基金

摘　　要：采用一种新颖的扩展卡尔曼滤波器(EKF)实现了对直线感应电动机的速度检测,并考虑边端效应的影响进行了修正。采用模拟退火遗传算法(SAGA)对EKF性能进行优化,并与遗传算法(GA)优化的EKF进行了比较,表明SAGA具有更强的寻优能力。包括电机参数变化、负载扰动等情况下的仿真结果证明了该方案的有效性。A speed estimation method of linear induction motor（LIM） using a novel extended kalman filter（EKF） was presented in this paper. The modification for dynamic end effect of LIM was designed to achieve exact estimation results when LIM ran at high speed. A new approach of optimizing the performance of the extended kalman filter using simulated annealing genetic algorithm （SAGA） was compared with the use of a genetic algorithm（GA）. The optimization techniques are verified effective by simulation on a field-oriented controller under various operating conditions including motor parameter sensitivity and load disturbance.

关 键 词：直线感应电动机 无速度传感器 扩展卡尔曼滤波 模拟退火遗传算法 

分 类 号：TM359.4[电气工程—电机] TM346