{"title":"感应电机磁链和转速估计的新算法","authors":"Yang Wenqiang, Jia Zhengchun, Xu Qiang","doi":"10.1109/ICEMS.2001.971772","DOIUrl":null,"url":null,"abstract":"A new reduced-order extended Kalman filter to estimate the rotor flux components and speed of an induction machine for speed sensorless vector control is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm, and verify the usefulness of the proposed algorithm.","PeriodicalId":143007,"journal":{"name":"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A new algorithm for flux and speed estimation in induction machine\",\"authors\":\"Yang Wenqiang, Jia Zhengchun, Xu Qiang\",\"doi\":\"10.1109/ICEMS.2001.971772\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new reduced-order extended Kalman filter to estimate the rotor flux components and speed of an induction machine for speed sensorless vector control is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm, and verify the usefulness of the proposed algorithm.\",\"PeriodicalId\":143007,\"journal\":{\"name\":\"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEMS.2001.971772\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMS.2001.971772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new algorithm for flux and speed estimation in induction machine
A new reduced-order extended Kalman filter to estimate the rotor flux components and speed of an induction machine for speed sensorless vector control is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm, and verify the usefulness of the proposed algorithm.
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