{"title":"基于人工神经网络的内置式永磁同步电机转速控制实验实现","authors":"M.A. Rahman, M. Hoque","doi":"10.1109/IEMDC.1997.604180","DOIUrl":null,"url":null,"abstract":"This paper presents a laboratory implementation of a novel speed control scheme for an interior-type permanent magnet synchronous motor using a self-tuning artificial neural network. The newly devised artificial neural network control structure based on the inverse motor dynamics and nonlinear load characteristics has been realized in real-time using a digital signal processor controller board DS-1102.","PeriodicalId":176640,"journal":{"name":"1997 IEEE International Electric Machines and Drives Conference Record","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experimental implementation of ANN based speed control for interior-type permanent magnet synchronous motors\",\"authors\":\"M.A. Rahman, M. Hoque\",\"doi\":\"10.1109/IEMDC.1997.604180\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a laboratory implementation of a novel speed control scheme for an interior-type permanent magnet synchronous motor using a self-tuning artificial neural network. The newly devised artificial neural network control structure based on the inverse motor dynamics and nonlinear load characteristics has been realized in real-time using a digital signal processor controller board DS-1102.\",\"PeriodicalId\":176640,\"journal\":{\"name\":\"1997 IEEE International Electric Machines and Drives Conference Record\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1997 IEEE International Electric Machines and Drives Conference Record\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMDC.1997.604180\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1997 IEEE International Electric Machines and Drives Conference Record","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMDC.1997.604180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Experimental implementation of ANN based speed control for interior-type permanent magnet synchronous motors
This paper presents a laboratory implementation of a novel speed control scheme for an interior-type permanent magnet synchronous motor using a self-tuning artificial neural network. The newly devised artificial neural network control structure based on the inverse motor dynamics and nonlinear load characteristics has been realized in real-time using a digital signal processor controller board DS-1102.
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