{"title":"Design of fuzzy logic control of permanent magnet DC motor under real constraints and disturbances","authors":"J. Velagić, A. Galijasevic","doi":"10.1109/CCA.2009.5281099","DOIUrl":null,"url":null,"abstract":"This paper presents a design of the fuzzy logic control for a permanent magnet DC motor. The main objective is to achieve a robust controller under disturbances and unmodeled dynamics acting, such as load torque, dead zone, measurement noise and nonlinearities. The whole system contains the DC motor, driver, tachogenerator, external load and microprocessor based system (dSPACE CLP1004). This system is considered such as black box. The fuzzy controller is designed in simulation mode first. The model of whole system was obtained through identification procedure. Then this fuzzy controller is included into a real physical control structure. Control performance of the fuzzy controller in both simulation and experimental modes are compared under mentioned constraints. Also, results obtained by the fuzzy controller are compared with the same obtained by PID controller.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCA.2009.5281099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
This paper presents a design of the fuzzy logic control for a permanent magnet DC motor. The main objective is to achieve a robust controller under disturbances and unmodeled dynamics acting, such as load torque, dead zone, measurement noise and nonlinearities. The whole system contains the DC motor, driver, tachogenerator, external load and microprocessor based system (dSPACE CLP1004). This system is considered such as black box. The fuzzy controller is designed in simulation mode first. The model of whole system was obtained through identification procedure. Then this fuzzy controller is included into a real physical control structure. Control performance of the fuzzy controller in both simulation and experimental modes are compared under mentioned constraints. Also, results obtained by the fuzzy controller are compared with the same obtained by PID controller.