R. Sakthivel, P. Selvaraj, Yeong-Jae Kim, Dong-Hoon Lee, O. Kwon, R. Sakthivel
{"title":"Robust $ H_\\infty $ resilient event-triggered control design for T-S fuzzy systems","authors":"R. Sakthivel, P. Selvaraj, Yeong-Jae Kim, Dong-Hoon Lee, O. Kwon, R. Sakthivel","doi":"10.3934/dcdss.2022028","DOIUrl":null,"url":null,"abstract":"<p style='text-indent:20px;'>This paper investigates the resilient <inline-formula><tex-math id=\"M2\">\\begin{document}$ H_\\infty $\\end{document}</tex-math></inline-formula> event-triggered control problem for Takagi-Sugeno fuzzy system with time-varying delay and external disturbance. Contrary to some existing results, the considered event-triggered conditions are verified only at each sampling instant because it is difficult to prove Zeno-freeness for a continuous event-triggered mechanism in the presence of external disturbance. Furthermore, by constructing an appropriate Lyapunov-Krasovskii functional, sufficient conditions are derived in the form of linear matrix inequalities to ensure the asymptotic stability and the <inline-formula><tex-math id=\"M3\">\\begin{document}$ H_\\infty $\\end{document}</tex-math></inline-formula> performances of closed-loop systems. More precisely, the proposed control design not only improve robust performance but also save the communication resources. Finally, the obtained theoretical results are verified through numerical simulation, which demonstrate the efficiency and advantages of the proposed method.</p>","PeriodicalId":11254,"journal":{"name":"Discrete & Continuous Dynamical Systems - S","volume":"43 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discrete & Continuous Dynamical Systems - S","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3934/dcdss.2022028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper investigates the resilient \begin{document}$ H_\infty $\end{document} event-triggered control problem for Takagi-Sugeno fuzzy system with time-varying delay and external disturbance. Contrary to some existing results, the considered event-triggered conditions are verified only at each sampling instant because it is difficult to prove Zeno-freeness for a continuous event-triggered mechanism in the presence of external disturbance. Furthermore, by constructing an appropriate Lyapunov-Krasovskii functional, sufficient conditions are derived in the form of linear matrix inequalities to ensure the asymptotic stability and the \begin{document}$ H_\infty $\end{document} performances of closed-loop systems. More precisely, the proposed control design not only improve robust performance but also save the communication resources. Finally, the obtained theoretical results are verified through numerical simulation, which demonstrate the efficiency and advantages of the proposed method.
This paper investigates the resilient \begin{document}$ H_\infty $\end{document} event-triggered control problem for Takagi-Sugeno fuzzy system with time-varying delay and external disturbance. Contrary to some existing results, the considered event-triggered conditions are verified only at each sampling instant because it is difficult to prove Zeno-freeness for a continuous event-triggered mechanism in the presence of external disturbance. Furthermore, by constructing an appropriate Lyapunov-Krasovskii functional, sufficient conditions are derived in the form of linear matrix inequalities to ensure the asymptotic stability and the \begin{document}$ H_\infty $\end{document} performances of closed-loop systems. More precisely, the proposed control design not only improve robust performance but also save the communication resources. Finally, the obtained theoretical results are verified through numerical simulation, which demonstrate the efficiency and advantages of the proposed method.