{"title":"Extended Kalman filter tuning in sensorless PMSM drives","authors":"S. Bolognani, L. Tubiana, M. Zigliotto","doi":"10.1109/PCC.2002.998560","DOIUrl":null,"url":null,"abstract":"The use of an extended Kalman filter (EKF) as nonlinear speed and position observer for permanent magnet synchronous motor (PMSM) drives is a mature research topic. Notwithstanding, the shift from research prototype to a market-ready product still calls for a solution of some implementation pitfalls. The major and still unsolved topic is the choice of the EKF covariance matrices. This paper replaces the usual trial-and-error method with a straightforward matrices choice. These matrices, possibly combined with a novel self-tuning procedure, should put the EKF drive much closer to an off-the-shelf product. The proposed method is based on the complete normalisation of the EKF algorithm representation. Successful experimental results are included in the paper.","PeriodicalId":320424,"journal":{"name":"Proceedings of the Power Conversion Conference-Osaka 2002 (Cat. No.02TH8579)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"526","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Power Conversion Conference-Osaka 2002 (Cat. No.02TH8579)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCC.2002.998560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 526
Abstract
The use of an extended Kalman filter (EKF) as nonlinear speed and position observer for permanent magnet synchronous motor (PMSM) drives is a mature research topic. Notwithstanding, the shift from research prototype to a market-ready product still calls for a solution of some implementation pitfalls. The major and still unsolved topic is the choice of the EKF covariance matrices. This paper replaces the usual trial-and-error method with a straightforward matrices choice. These matrices, possibly combined with a novel self-tuning procedure, should put the EKF drive much closer to an off-the-shelf product. The proposed method is based on the complete normalisation of the EKF algorithm representation. Successful experimental results are included in the paper.