K. Inoue, Junnji Yoshitugu, S. Shirogane, P. Boyagoda, M. Nakaoka
{"title":"AC servo motor drive systems using auto-tuning gain parameter processor with automatic learning control scheme","authors":"K. Inoue, Junnji Yoshitugu, S. Shirogane, P. Boyagoda, M. Nakaoka","doi":"10.1109/ISIE.1997.648871","DOIUrl":null,"url":null,"abstract":"In this paper, an advanced control method of system parameter auto-tuning implementation for an AC servo system using fuzzy reasoning logic with an automatic learning control function is described. This method includes three features: (i) it is not necessary to input some kinds of fuzzy rules to the servo system before starting auto-tuning operation, thus, the fuzzy rules can be automatically produced in logical process learning; (ii) knowledge and information about the system parameter tuning technique are not required; and (iii) both high speed response and robustness can be obtained. The feasible effectiveness of this auto-tuning processing approach for an AC servo system are practically confirmed through experimental results.","PeriodicalId":134474,"journal":{"name":"ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics","volume":"196 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.1997.648871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, an advanced control method of system parameter auto-tuning implementation for an AC servo system using fuzzy reasoning logic with an automatic learning control function is described. This method includes three features: (i) it is not necessary to input some kinds of fuzzy rules to the servo system before starting auto-tuning operation, thus, the fuzzy rules can be automatically produced in logical process learning; (ii) knowledge and information about the system parameter tuning technique are not required; and (iii) both high speed response and robustness can be obtained. The feasible effectiveness of this auto-tuning processing approach for an AC servo system are practically confirmed through experimental results.