{"title":"感应电机的无传感器间接神经控制","authors":"Zhivko Zhekov","doi":"10.1109/ET.2018.8549639","DOIUrl":null,"url":null,"abstract":"In this article is presented indirect adaptive neural sensorless control in combination with vector principle for induction motor control. Control system containing neural controllers of the speed and flux channels. Neural speed estimator is designed as a neural model of the plant. For the controllers and estimator are used on-line trained backpropagation neural networks. Simulation research confirmed sufficient system performance at wide range input signal variation is done.","PeriodicalId":374877,"journal":{"name":"2018 IEEE XXVII International Scientific Conference Electronics - ET","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Sensorless Indirect Neural Control of Induction Motor\",\"authors\":\"Zhivko Zhekov\",\"doi\":\"10.1109/ET.2018.8549639\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article is presented indirect adaptive neural sensorless control in combination with vector principle for induction motor control. Control system containing neural controllers of the speed and flux channels. Neural speed estimator is designed as a neural model of the plant. For the controllers and estimator are used on-line trained backpropagation neural networks. Simulation research confirmed sufficient system performance at wide range input signal variation is done.\",\"PeriodicalId\":374877,\"journal\":{\"name\":\"2018 IEEE XXVII International Scientific Conference Electronics - ET\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE XXVII International Scientific Conference Electronics - ET\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ET.2018.8549639\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE XXVII International Scientific Conference Electronics - ET","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ET.2018.8549639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sensorless Indirect Neural Control of Induction Motor
In this article is presented indirect adaptive neural sensorless control in combination with vector principle for induction motor control. Control system containing neural controllers of the speed and flux channels. Neural speed estimator is designed as a neural model of the plant. For the controllers and estimator are used on-line trained backpropagation neural networks. Simulation research confirmed sufficient system performance at wide range input signal variation is done.