Adaptive Fuzzy Secure Collision-Free Formation Control for Nonlinear MASs With DoS Attacks

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Jun Zhang;Jun Ning;Shaocheng Tong
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引用次数: 0

Abstract

In this article, the collision-free adaptive fuzzy secure formation control problem is investigated for uncertain nonlinear multiagent systems (MASs) under denial-of-service (DoS) attacks. Since the DoS attacks block the signal transmission between agents, the leader’s states and output are inaccessible to the followers, a distributed command governor is designed to estimate them. To avoid the collisions among the agents or between the agents and the dynamics obstacles, the integral-type barrier Lyapunov function (BLF) is employed to develop a secure collision-free adaptive fuzzy formation controller based on the designed governor. It is shown that the developed secure collision-free formation control approach can not only achieve the formation objective, but also avoid the collisions under DoS attacks. Finally, we apply the developed secure collision free formation control method to multiple Euler-Lagrangian (EL) systems, the simulation and comparison results verify its effectiveness.
具有DoS攻击的非线性质量的自适应模糊安全无碰撞编队控制
研究了不确定非线性多智能体系统在拒绝服务攻击下的无碰撞自适应模糊安全编队控制问题。由于DoS攻击阻断了agent之间的信号传输,follower无法获取leader的状态和输出,因此设计了分布式命令调控器对其进行估计。为了避免智能体之间或智能体与动态障碍物之间的碰撞,采用积分型障碍Lyapunov函数(BLF),基于所设计的调速器开发了安全无碰撞的自适应模糊编队控制器。研究结果表明,所提出的安全无碰撞编队控制方法既能实现编队目标,又能避免DoS攻击下的编队冲突。最后,将所提出的安全无碰撞编队控制方法应用于多个欧拉-拉格朗日(EL)系统,仿真和对比结果验证了该方法的有效性。
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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