K. C. Draa, H. Voos, M. Alma, A. Zemouche, M. Darouach
{"title":"厌氧消化模型的离散非线性状态观测器","authors":"K. C. Draa, H. Voos, M. Alma, A. Zemouche, M. Darouach","doi":"10.1109/ICOSC.2017.7958714","DOIUrl":null,"url":null,"abstract":"This paper deals with the design of a discrete time nonlinear observer for an anaerobic digestion process. The designed observer is devoted to a general class of systems, precisely linear systems, LPV systems with known and bounded parameters, and nonlinear Lipschitz systems. In order to ensure stability of the estimation error, a new LMI condition is proposed. In this LMI, additional decision variables are included to enhance its feasibility. Indeed, this was possible due to the use of a suitable reformulation of the Young's inequality. Numerical simulations using the investigated two-step anaerobic digestion model show the effectiveness of the proposed LMI methodology.","PeriodicalId":113395,"journal":{"name":"2017 6th International Conference on Systems and Control (ICSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"LMI-based discrete-time nonlinear state observer for an anaerobic digestion model\",\"authors\":\"K. C. Draa, H. Voos, M. Alma, A. Zemouche, M. Darouach\",\"doi\":\"10.1109/ICOSC.2017.7958714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the design of a discrete time nonlinear observer for an anaerobic digestion process. The designed observer is devoted to a general class of systems, precisely linear systems, LPV systems with known and bounded parameters, and nonlinear Lipschitz systems. In order to ensure stability of the estimation error, a new LMI condition is proposed. In this LMI, additional decision variables are included to enhance its feasibility. Indeed, this was possible due to the use of a suitable reformulation of the Young's inequality. Numerical simulations using the investigated two-step anaerobic digestion model show the effectiveness of the proposed LMI methodology.\",\"PeriodicalId\":113395,\"journal\":{\"name\":\"2017 6th International Conference on Systems and Control (ICSC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 6th International Conference on Systems and Control (ICSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSC.2017.7958714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Systems and Control (ICSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSC.2017.7958714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
LMI-based discrete-time nonlinear state observer for an anaerobic digestion model
This paper deals with the design of a discrete time nonlinear observer for an anaerobic digestion process. The designed observer is devoted to a general class of systems, precisely linear systems, LPV systems with known and bounded parameters, and nonlinear Lipschitz systems. In order to ensure stability of the estimation error, a new LMI condition is proposed. In this LMI, additional decision variables are included to enhance its feasibility. Indeed, this was possible due to the use of a suitable reformulation of the Young's inequality. Numerical simulations using the investigated two-step anaerobic digestion model show the effectiveness of the proposed LMI methodology.