Rongmei Li, Xin Huo, Weizhen Liu, Kemao Ma, Ruihang Ji
{"title":"Adaptive Fuzzy Secure Consensus Control of Switched Filter-Based High-Order Fully Actuated MASs Under DoS Attacks","authors":"Rongmei Li, Xin Huo, Weizhen Liu, Kemao Ma, Ruihang Ji","doi":"10.1002/rnc.70680","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This paper addresses the adaptive secure consensus control of high-order fully actuated multi-agent systems (MASs) under denial-of-service (DoS) attacks. To deal with the transmitted data from the leader and neighbors which are unavailable in the presence of DoS attacks, an observer-based switched filter is proposed to estimate the output of the system and its high-order derivatives, which switches between intervals with and without attacks, making zero estimation errors possible. This active switching mechanism ensures zero estimation errors and effectively accommodates the attack impacts. Then, a high-gain observer based on a differentiator is designed to avoid the differential explosion problem and the adaptive parameters are designed to fit the weights of fuzzy logic systems (FLSs) to approximate the unknown nonlinearity when the high-order backstepping technique is applied. Unlike classical state-space methods, which require transforming the model into a first-order system and only consider first-order state consensus, a controller based on the fully actuated characteristic is subsequently proposed to ensure high-order state consensus of the MASs. It is strictly demonstrated that all closed-loop variables achieve global uniform ultimate boundedness, with the consensus tracking errors asymptotically converging to zero under DoS attacks. Ultimately, the effectiveness of the proposed control method is illustrated through a numerical simulation.</p>\n </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7727-7744"},"PeriodicalIF":3.1000,"publicationDate":"2026-10-12","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.70680","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/26 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper addresses the adaptive secure consensus control of high-order fully actuated multi-agent systems (MASs) under denial-of-service (DoS) attacks. To deal with the transmitted data from the leader and neighbors which are unavailable in the presence of DoS attacks, an observer-based switched filter is proposed to estimate the output of the system and its high-order derivatives, which switches between intervals with and without attacks, making zero estimation errors possible. This active switching mechanism ensures zero estimation errors and effectively accommodates the attack impacts. Then, a high-gain observer based on a differentiator is designed to avoid the differential explosion problem and the adaptive parameters are designed to fit the weights of fuzzy logic systems (FLSs) to approximate the unknown nonlinearity when the high-order backstepping technique is applied. Unlike classical state-space methods, which require transforming the model into a first-order system and only consider first-order state consensus, a controller based on the fully actuated characteristic is subsequently proposed to ensure high-order state consensus of the MASs. It is strictly demonstrated that all closed-loop variables achieve global uniform ultimate boundedness, with the consensus tracking errors asymptotically converging to zero under DoS attacks. Ultimately, the effectiveness of the proposed control method is illustrated through a numerical simulation.
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.