{"title":"多代理系统抵御混合攻击的弹性时变编队追踪技术在航天器编队中的应用","authors":"Yukang Cui;Yihui Huang;Qin Zhao;Xian Yu;Tingwen Huang","doi":"10.1109/TCYB.2024.3492035","DOIUrl":null,"url":null,"abstract":"This work investigates the time-varying formation-tracking problem of multiagent systems under hybrid attacks, including denial-of-service (DoS) attacks and actuation attacks. State estimators are designed for each node of the swarm leveraging relative information from neighboring estimators to generate the desired positional states for formation tracking. The direct use of corrupted consensus control inputs is avoided, thereby defending against actuation attacks targeted at node input signals. Furthermore, we propose an event-triggered protocol with a sampling mechanism to enhance resilience against DoS attacks on communication with neighboring estimators equipped with a topology recovery policy. This resilient protocol against DoS attacks is fully distributed and does not require prior knowledge of network topology, making it scalable to large networks. Finally, an adaptive attack-resilient control scheme is introduced to counteract potential unbounded actuation attacks via output feedback, enabling each follower to track the positional states provided by the distributed estimators. The tracking error is proven to be uniformly ultimately bounded. The proposed event-triggered hierarchical control scheme is validated through its application to spacecraft formation.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 2","pages":"625-637"},"PeriodicalIF":9.4000,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Resilient Time-Varying Formation-Tracking of Multiagent Systems Against Hybrid Attacks With Applications to Spacecraft Formation\",\"authors\":\"Yukang Cui;Yihui Huang;Qin Zhao;Xian Yu;Tingwen Huang\",\"doi\":\"10.1109/TCYB.2024.3492035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work investigates the time-varying formation-tracking problem of multiagent systems under hybrid attacks, including denial-of-service (DoS) attacks and actuation attacks. State estimators are designed for each node of the swarm leveraging relative information from neighboring estimators to generate the desired positional states for formation tracking. The direct use of corrupted consensus control inputs is avoided, thereby defending against actuation attacks targeted at node input signals. Furthermore, we propose an event-triggered protocol with a sampling mechanism to enhance resilience against DoS attacks on communication with neighboring estimators equipped with a topology recovery policy. This resilient protocol against DoS attacks is fully distributed and does not require prior knowledge of network topology, making it scalable to large networks. Finally, an adaptive attack-resilient control scheme is introduced to counteract potential unbounded actuation attacks via output feedback, enabling each follower to track the positional states provided by the distributed estimators. The tracking error is proven to be uniformly ultimately bounded. The proposed event-triggered hierarchical control scheme is validated through its application to spacecraft formation.\",\"PeriodicalId\":13112,\"journal\":{\"name\":\"IEEE Transactions on Cybernetics\",\"volume\":\"55 2\",\"pages\":\"625-637\"},\"PeriodicalIF\":9.4000,\"publicationDate\":\"2024-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Cybernetics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10767854/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cybernetics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10767854/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Resilient Time-Varying Formation-Tracking of Multiagent Systems Against Hybrid Attacks With Applications to Spacecraft Formation
This work investigates the time-varying formation-tracking problem of multiagent systems under hybrid attacks, including denial-of-service (DoS) attacks and actuation attacks. State estimators are designed for each node of the swarm leveraging relative information from neighboring estimators to generate the desired positional states for formation tracking. The direct use of corrupted consensus control inputs is avoided, thereby defending against actuation attacks targeted at node input signals. Furthermore, we propose an event-triggered protocol with a sampling mechanism to enhance resilience against DoS attacks on communication with neighboring estimators equipped with a topology recovery policy. This resilient protocol against DoS attacks is fully distributed and does not require prior knowledge of network topology, making it scalable to large networks. Finally, an adaptive attack-resilient control scheme is introduced to counteract potential unbounded actuation attacks via output feedback, enabling each follower to track the positional states provided by the distributed estimators. The tracking error is proven to be uniformly ultimately bounded. The proposed event-triggered hierarchical control scheme is validated through its application to spacecraft formation.
期刊介绍:
The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.