{"title":"一类非线性系统的神经网络动态建模与控制","authors":"A. Abdulaziz, M. Farsi","doi":"10.1109/ISIE.1993.268747","DOIUrl":null,"url":null,"abstract":"The paper describes a new neural network Controller using an IMC structure (NIMC). The structure is suitable for control of discrete-time SISO systems containing nonlinearities. Two design steps are assumed: (1) the controller is designed for optimal set-point tracking and disturbance rejection or model uncertainty and (2) the controller is detuned for robust performance. Comparative studies between NIMC and a conventional nonlinear adaptive controller is made.<<ETX>>","PeriodicalId":267349,"journal":{"name":"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic modelling and control for a class of non-linear systems using neural nets\",\"authors\":\"A. Abdulaziz, M. Farsi\",\"doi\":\"10.1109/ISIE.1993.268747\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes a new neural network Controller using an IMC structure (NIMC). The structure is suitable for control of discrete-time SISO systems containing nonlinearities. Two design steps are assumed: (1) the controller is designed for optimal set-point tracking and disturbance rejection or model uncertainty and (2) the controller is detuned for robust performance. Comparative studies between NIMC and a conventional nonlinear adaptive controller is made.<<ETX>>\",\"PeriodicalId\":267349,\"journal\":{\"name\":\"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIE.1993.268747\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.1993.268747","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic modelling and control for a class of non-linear systems using neural nets
The paper describes a new neural network Controller using an IMC structure (NIMC). The structure is suitable for control of discrete-time SISO systems containing nonlinearities. Two design steps are assumed: (1) the controller is designed for optimal set-point tracking and disturbance rejection or model uncertainty and (2) the controller is detuned for robust performance. Comparative studies between NIMC and a conventional nonlinear adaptive controller is made.<>
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