{"title":"Aperiodic Sampled-Data-Based Resilient Control for a Class of Switched Nonlinear Systems Against Denial-Of-Service Attacks","authors":"Chunyan Wang, Xinrong Fan, Yifan Fu","doi":"10.1002/rnc.7944","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This paper investigates an aperiodic sampled-data-based resilient control problem for a class of non-strict feedback switched systems under denial-of-service (DoS) attacks. If the output values can be available only at the sampling instants, such incomplete information will make the variable non-differentiable and increase the risk of asynchronous operation for switched systems. Moreover, it will become more serious if DoS attacks destroy both the switching and output signals. To address these challenges, a novel aperiodic sampling rule is designed. Based on the assigned sampling rule, a sampled-data observer and an adaptive resilient controller are constructed, which not only reduce the dual-channel transmission burden, eliminate the trouble of output being not-differentiable, but also overcome the adverse impact of DoS attacks. What's more, the proposed sampling rule and the control strategy, relating to the switching signal, highlight the characteristics of each subsystem. The common Lyapunov stability theory can ensure all the variables of the considered closed-loop switched systems are bounded under arbitrary switching. Finally, the simulation results of two examples are given to verify the effectiveness of the proposed method.</p>\n </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 11","pages":"4809-4825"},"PeriodicalIF":3.2000,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Robust and Nonlinear Control","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/rnc.7944","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper investigates an aperiodic sampled-data-based resilient control problem for a class of non-strict feedback switched systems under denial-of-service (DoS) attacks. If the output values can be available only at the sampling instants, such incomplete information will make the variable non-differentiable and increase the risk of asynchronous operation for switched systems. Moreover, it will become more serious if DoS attacks destroy both the switching and output signals. To address these challenges, a novel aperiodic sampling rule is designed. Based on the assigned sampling rule, a sampled-data observer and an adaptive resilient controller are constructed, which not only reduce the dual-channel transmission burden, eliminate the trouble of output being not-differentiable, but also overcome the adverse impact of DoS attacks. What's more, the proposed sampling rule and the control strategy, relating to the switching signal, highlight the characteristics of each subsystem. The common Lyapunov stability theory can ensure all the variables of the considered closed-loop switched systems are bounded under arbitrary switching. Finally, the simulation results of two examples are given to verify the effectiveness of the proposed method.
期刊介绍:
Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.