电工技术学报2017，Vol.32Issue(5)：86-96,11.
STEKF协同残差归一化的感应电机转速辨识方法
A Speed Estimation Method Based on Strong Tracking Extended Kalman Filter with Normalized Residuals for Induction Motors
摘要
Abstract
To improve the performance of sensorless induction motor(IM)drives,an adaptive speed estimation method based on the strong tracking extended Kalman filter with normalized residuals algorithm(NR-STEKF)for induction motors is proposed in this paper.With this method,the fading factor is introduced into the covariance matrix of the predicted state,which forces the residual sequences orthogonal to each other and tunes the gain matrix online.Simultaneously,the fading factor can be continuously self-tuned with the normalized residuals algorithm,and the information asymmetry which is caused by the residual numerical difference is eliminated.Therefore,the proposed method improves the model adaptability to the actual systems and the environmental variations,reduces the speed estimation error,and can satisfy the estimation request running at low speed.The correctness and the effectiveness of the proposed method are verified by the experimental results.关键词
强跟踪扩展卡尔曼滤波/残差归一化/自适应转速估计/渐消因子Key words
Strong tracking extended Kalman filter(STEKF)/normalized residuals(NR)/adaptive speed estimation/fading factor分类
信息技术与安全科学引用本文复制引用
尹忠刚,李国银,张延庆,孙向东,钟彦儒..STEKF协同残差归一化的感应电机转速辨识方法[J].电工技术学报,2017,32(5):86-96,11.基金项目
国家自然科学基金项目(51307139)、陕西省青年科技新星资助项目(2015KJXX-29)和陕西省工业攻关项目(2014K08-30)资助. （51307139）
