{"title":"一类基于神经网络的非线性系统自适应观测器","authors":"J. Choi, J. Farrell","doi":"10.1109/ISIC.1999.796640","DOIUrl":null,"url":null,"abstract":"This paper presents an adaptive observer using neural networks for a class of nonlinear systems. The adaptive observer follows the nonlinear model estimation method for automated fault diagnosis. The contributions of this article include: modification of the estimation model as appropriate for certain nonlinear control applications; modification of the stability proofs; investigation of the observer performance through an illustrative simulation.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Adaptive observer for a class of nonlinear systems using neural networks\",\"authors\":\"J. Choi, J. Farrell\",\"doi\":\"10.1109/ISIC.1999.796640\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an adaptive observer using neural networks for a class of nonlinear systems. The adaptive observer follows the nonlinear model estimation method for automated fault diagnosis. The contributions of this article include: modification of the estimation model as appropriate for certain nonlinear control applications; modification of the stability proofs; investigation of the observer performance through an illustrative simulation.\",\"PeriodicalId\":300130,\"journal\":{\"name\":\"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.1999.796640\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.1999.796640","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive observer for a class of nonlinear systems using neural networks
This paper presents an adaptive observer using neural networks for a class of nonlinear systems. The adaptive observer follows the nonlinear model estimation method for automated fault diagnosis. The contributions of this article include: modification of the estimation model as appropriate for certain nonlinear control applications; modification of the stability proofs; investigation of the observer performance through an illustrative simulation.
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