D. Jukić, T. Varga, T. Benšić, V. J. Štil, M. Barukčić
{"title":"MODELING AND FUZZY CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTORS","authors":"D. Jukić, T. Varga, T. Benšić, V. J. Štil, M. Barukčić","doi":"10.1049/icp.2021.1097","DOIUrl":null,"url":null,"abstract":"This paper deals with Permanent Magnet Synchronous Motor modeling and control. The derived nonlinear dq model is a combination of Finite Element Method simulation data with the classical dq model. The so derived model keeps the precision of the Finite Element Method simulations and also the fast execution times of the dq model. The Finite Element Method data is included in the dq model using Artificial Neural Networks. The derived model is also used for controller design. The chosen controller is a PI like Fuzzy Logic Controller, which is tuned using Genetic Algorithm optimization. The Permanent Magnet Synchronous Motor with Fuzzy Logic Controller operation is tested using Real-Time (Model-in-the-Loop) simulations.","PeriodicalId":188371,"journal":{"name":"The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020)","volume":"39 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/icp.2021.1097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper deals with Permanent Magnet Synchronous Motor modeling and control. The derived nonlinear dq model is a combination of Finite Element Method simulation data with the classical dq model. The so derived model keeps the precision of the Finite Element Method simulations and also the fast execution times of the dq model. The Finite Element Method data is included in the dq model using Artificial Neural Networks. The derived model is also used for controller design. The chosen controller is a PI like Fuzzy Logic Controller, which is tuned using Genetic Algorithm optimization. The Permanent Magnet Synchronous Motor with Fuzzy Logic Controller operation is tested using Real-Time (Model-in-the-Loop) simulations.