K. Inoue, J. Yoshitsugu, S. Shirogane, P. Boyagoda, M. Nakaoka
{"title":"DC brush-less servo motor drive systems using automatic learning control-based auto gain parameter tuning scheme","authors":"K. Inoue, J. Yoshitsugu, S. Shirogane, P. Boyagoda, M. Nakaoka","doi":"10.1109/IECON.1997.668414","DOIUrl":null,"url":null,"abstract":"In this paper, the authors describe an advanced control method of system parameter auto-tuning implementation for a DC brushless motor drive system using fuzzy reasoning logic with an automatic learning control function. This method includes three features: (i) it is not necessary to input some kind of fuzzy rule to the servo system before starting autotuning operation; thus fuzzy rules can be automatically produced in learning a logical process; (ii) no knowledge or information of system parameter tuning techniques are required; and (iii) both high speed response and robustness can be obtained. The feasible effectiveness of this auto-tuning processing approach for DC brushless servomotor drives are practically confirmed through experimental results.","PeriodicalId":404447,"journal":{"name":"Proceedings of the IECON'97 23rd International Conference on Industrial Electronics, Control, and Instrumentation (Cat. No.97CH36066)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IECON'97 23rd International Conference on Industrial Electronics, Control, and Instrumentation (Cat. No.97CH36066)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.1997.668414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, the authors describe an advanced control method of system parameter auto-tuning implementation for a DC brushless motor drive system using fuzzy reasoning logic with an automatic learning control function. This method includes three features: (i) it is not necessary to input some kind of fuzzy rule to the servo system before starting autotuning operation; thus fuzzy rules can be automatically produced in learning a logical process; (ii) no knowledge or information of system parameter tuning techniques are required; and (iii) both high speed response and robustness can be obtained. The feasible effectiveness of this auto-tuning processing approach for DC brushless servomotor drives are practically confirmed through experimental results.