{"title":"基于观测器的内嵌式永磁电机位置和速度估计","authors":"B. Singh, P. Gaur, A. Mittal","doi":"10.1109/PEDES.2006.344355","DOIUrl":null,"url":null,"abstract":"This paper presents position sensorless interior permanent magnet synchronous motor drive using a discretized extended kalman filter algorithm (EKF). An observer based speed estimator which can be used for the state estimation of a non linear dynamic system in real time is presented here. Speed and position estimation of IPM is simulated using MATLAB and results of step variation in speed, load perturbation and flux weakening are presented to substantiate the proposed estimation of the speed.","PeriodicalId":262597,"journal":{"name":"2006 International Conference on Power Electronic, Drives and Energy Systems","volume":"10 12","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Observer Based Position and Speed Estimation of Interior Permanent Magnet Motor\",\"authors\":\"B. Singh, P. Gaur, A. Mittal\",\"doi\":\"10.1109/PEDES.2006.344355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents position sensorless interior permanent magnet synchronous motor drive using a discretized extended kalman filter algorithm (EKF). An observer based speed estimator which can be used for the state estimation of a non linear dynamic system in real time is presented here. Speed and position estimation of IPM is simulated using MATLAB and results of step variation in speed, load perturbation and flux weakening are presented to substantiate the proposed estimation of the speed.\",\"PeriodicalId\":262597,\"journal\":{\"name\":\"2006 International Conference on Power Electronic, Drives and Energy Systems\",\"volume\":\"10 12\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Power Electronic, Drives and Energy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PEDES.2006.344355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Power Electronic, Drives and Energy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PEDES.2006.344355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Observer Based Position and Speed Estimation of Interior Permanent Magnet Motor
This paper presents position sensorless interior permanent magnet synchronous motor drive using a discretized extended kalman filter algorithm (EKF). An observer based speed estimator which can be used for the state estimation of a non linear dynamic system in real time is presented here. Speed and position estimation of IPM is simulated using MATLAB and results of step variation in speed, load perturbation and flux weakening are presented to substantiate the proposed estimation of the speed.
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