C. C. Hernández, E. Sánchez, A. Loukianov, B. Castillo-Toledo
{"title":"基于循环高阶神经网络的直流电机实时转矩控制","authors":"C. C. Hernández, E. Sánchez, A. Loukianov, B. Castillo-Toledo","doi":"10.1109/CCA.2009.5280996","DOIUrl":null,"url":null,"abstract":"This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high order neural network (RHONN) to identify the plant model. Using this model, a control law is derived, which combines block control and sliding modes techniques. The applicability of the scheme is illustrated via real time implementation for a DC motor with separate winding excitation.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Real-time torque control for a DC motor using recurrent high order neural networks\",\"authors\":\"C. C. Hernández, E. Sánchez, A. Loukianov, B. Castillo-Toledo\",\"doi\":\"10.1109/CCA.2009.5280996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high order neural network (RHONN) to identify the plant model. Using this model, a control law is derived, which combines block control and sliding modes techniques. The applicability of the scheme is illustrated via real time implementation for a DC motor with separate winding excitation.\",\"PeriodicalId\":294950,\"journal\":{\"name\":\"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCA.2009.5280996\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCA.2009.5280996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time torque control for a DC motor using recurrent high order neural networks
This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high order neural network (RHONN) to identify the plant model. Using this model, a control law is derived, which combines block control and sliding modes techniques. The applicability of the scheme is illustrated via real time implementation for a DC motor with separate winding excitation.