E. Chiricozzi, F. Parasiliti, M. Tursini, D. Q. Zhang
{"title":"Fuzzy self-tuning PI control of PM synchronous motor drives","authors":"E. Chiricozzi, F. Parasiliti, M. Tursini, D. Q. Zhang","doi":"10.1109/PEDS.1995.404976","DOIUrl":null,"url":null,"abstract":"In this paper, a new gain self-tuning method for PI controllers based on the fuzzy inference mechanism has been proposed and implemented. The essential idea is to: (1) define a dynamically changed reference trajectory in the error and error derivative plain, known as a \"sliding trajectory\"; (2) compute the error area between the sliding trajectory and the effective one with a special algorithm, using this quantity as a performance index to evaluate the system response; (3) draw a fuzzy relationship between a PI gain correction parameter and the performance index; and (4) based on the fuzzy inference mechanism, PI gains are calculated and tuned. The proposed method has been verified through simulations using the speed control of a PM synchronous motor drive system as a testbed. The obtained results demonstrate the effectiveness of this novel method.<<ETX>>","PeriodicalId":244042,"journal":{"name":"Proceedings of 1995 International Conference on Power Electronics and Drive Systems. PEDS 95","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1995 International Conference on Power Electronics and Drive Systems. PEDS 95","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PEDS.1995.404976","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30
Abstract
In this paper, a new gain self-tuning method for PI controllers based on the fuzzy inference mechanism has been proposed and implemented. The essential idea is to: (1) define a dynamically changed reference trajectory in the error and error derivative plain, known as a "sliding trajectory"; (2) compute the error area between the sliding trajectory and the effective one with a special algorithm, using this quantity as a performance index to evaluate the system response; (3) draw a fuzzy relationship between a PI gain correction parameter and the performance index; and (4) based on the fuzzy inference mechanism, PI gains are calculated and tuned. The proposed method has been verified through simulations using the speed control of a PM synchronous motor drive system as a testbed. The obtained results demonstrate the effectiveness of this novel method.<>