{"title":"基于PI法的感应电机实时自整定控制器","authors":"S. Yaacob, F. Mohamed","doi":"10.1109/SICE.1999.788670","DOIUrl":null,"url":null,"abstract":"The self-tuning speed control of induction motor drives is presented using proportional plus integral (PI) method combined with the recursive least squares parameter estimation method to regulate the motor speed and load variation. To obtain good tracking and control characteristics, a PI self-tuning controller is adopted and the design procedure is developed for systematically finding its parameters according to the recursive least square method. The performance of the PI self-tuning controller greatly improves due to the integral action which eliminate the disturbance and the steady-state error. In addition, the RLS identification minimizes the error between the actual plant parameter and the recently estimated plant parameter.","PeriodicalId":103164,"journal":{"name":"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Real time self tuning controller for induction motor based on PI method\",\"authors\":\"S. Yaacob, F. Mohamed\",\"doi\":\"10.1109/SICE.1999.788670\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The self-tuning speed control of induction motor drives is presented using proportional plus integral (PI) method combined with the recursive least squares parameter estimation method to regulate the motor speed and load variation. To obtain good tracking and control characteristics, a PI self-tuning controller is adopted and the design procedure is developed for systematically finding its parameters according to the recursive least square method. The performance of the PI self-tuning controller greatly improves due to the integral action which eliminate the disturbance and the steady-state error. In addition, the RLS identification minimizes the error between the actual plant parameter and the recently estimated plant parameter.\",\"PeriodicalId\":103164,\"journal\":{\"name\":\"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SICE.1999.788670\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SICE.1999.788670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real time self tuning controller for induction motor based on PI method
The self-tuning speed control of induction motor drives is presented using proportional plus integral (PI) method combined with the recursive least squares parameter estimation method to regulate the motor speed and load variation. To obtain good tracking and control characteristics, a PI self-tuning controller is adopted and the design procedure is developed for systematically finding its parameters according to the recursive least square method. The performance of the PI self-tuning controller greatly improves due to the integral action which eliminate the disturbance and the steady-state error. In addition, the RLS identification minimizes the error between the actual plant parameter and the recently estimated plant parameter.