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.
出处
《微特电机》
北大核心
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
