{"title":"No load Robustness Analysis of AI Based Controllers & Estimators for SRM Drive","authors":"S. Bishnoi, R. Kumar, R. A. Gupta","doi":"10.1145/2979779.2979888","DOIUrl":null,"url":null,"abstract":"In this paper no-load robustness analysis of Artificial Intelligence (AI) based drives using four phases 8/6 poles Switched Reluctance Motor (SRM). Models of SR motor, AI based controllers i.e. fuzzy, ANN & ANFIS and AI based angle estimators i.e. fuzzy, ANN & ANFIS were developed and integrated as fuzzy-fuzzy, ANNANN & ANFIS-ANFIS SRM drives. Simulation of drives has been done for robustness performance of the drives and compared results. Robustness of drives are tested by varying switched reluctance motor physical parameters, including phase winding resistance (R), damping constant (F) and rotor inertia (J) in the SRM model. Robustness performance at startup and steady-state conditions at 500 rpm has been obtained by simulating these drives for no-load condition. Robustness performance has been plotted and compared to figure-out most robust AI based SRM drive.","PeriodicalId":298730,"journal":{"name":"Proceedings of the International Conference on Advances in Information Communication Technology & Computing","volume":"194 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Advances in Information Communication Technology & Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2979779.2979888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper no-load robustness analysis of Artificial Intelligence (AI) based drives using four phases 8/6 poles Switched Reluctance Motor (SRM). Models of SR motor, AI based controllers i.e. fuzzy, ANN & ANFIS and AI based angle estimators i.e. fuzzy, ANN & ANFIS were developed and integrated as fuzzy-fuzzy, ANNANN & ANFIS-ANFIS SRM drives. Simulation of drives has been done for robustness performance of the drives and compared results. Robustness of drives are tested by varying switched reluctance motor physical parameters, including phase winding resistance (R), damping constant (F) and rotor inertia (J) in the SRM model. Robustness performance at startup and steady-state conditions at 500 rpm has been obtained by simulating these drives for no-load condition. Robustness performance has been plotted and compared to figure-out most robust AI based SRM drive.
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