具有DoS攻击的异构多智能体系统的自适应二部时变编队跟踪控制。

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Chengmei Tang , Lianghao Ji , Shasha Yang , Xing Guo
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引用次数: 0

摘要

复杂网络中可能存在DoS (Denial-of-service,拒绝服务)攻击和对抗交互,破坏agent之间的协作通信,无法实现协同任务。因此,本文研究了具有DoS攻击和合作-对抗相互作用的异构多智能体系统(HMASs)的时变编队跟踪问题。它旨在保证系统通信的连通性,并允许追随者实现分布式安全的二部TVFT。为了使follower能够顺利获得leader的未知状态,设计了一种复合自适应动态事件触发(DET)二部补偿器。与现有补偿器相比,该补偿器能够抵抗DoS攻击;获取非自治领导者的信息;增加事件触发间隔;并且不依赖于有向图的全局信息。基于所提出的补偿器,设计了一种新的分布式编队控制器来实现TVFT。结果表明,得到了在DoS攻击下实现HMASs安全二部TVFT的充分条件和实现时变编队的可行性条件。同时,通过仿真验证了补偿器和控制器的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive bipartite time-varying formation tracking control for heterogeneous multi-agent systems with DoS attacks
Denial-of-service (DoS) attacks and antagonistic interactions may exist in complex networks, which will destroy cooperative communication between agents and thus cannot realize collaborative tasks. Therefore, this paper studies time-varying formation tracking (TVFT) of heterogeneous multi-agent systems (HMASs) with DoS attacks and cooperative-antagonistic interactions. It aims to ensure system communication connectivity and allow followers to achieve distributed secure bipartite TVFT. To enable followers to successfully obtain unknown state of the leader, this paper designs a composite adaptive dynamic event-triggered (DET) bipartite compensator. Compared with existing compensators, it can resist DoS attacks; obtain information of a non-autonomous leader; increase the event triggering interval; and be independent of global information of signed digraph. Based on proposed compensator, a new distributed formation controller is designed for achieving TVFT. The results show that sufficient conditions for realizing secure bipartite TVFT of HMASs under DoS attacks and feasibility conditions for realizing time-varying formations are obtained. Meanwhile, simulations are performed to test validity of the compensator and controller.
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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