基于DoS攻击和异步半马尔可夫链的全异构质量自适应弹性柔性控制。

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Dongxue Jiang, Guoguang Wen, Ahmed Rahmani, Sara Ifqir, Christophe Sueur, Tingwen Huang
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引用次数: 0

摘要

研究了随机交换拓扑和拒绝服务攻击下半马尔可夫跳变全异构多智能体系统(FHMASs)的自适应弹性柔性输出遏制(FOC)控制问题。与大多数现有的遏制控制结果相比,所提出的控制策略可以解决多智能体系统(MASs)完全异质性带来的挑战,特别是当多个领导者表现出不同的系统动力学时。为了更好地反映现实世界的质量和通信网络,首次采用多个异步半马尔可夫链来捕获系统参数变化和通信拓扑切换,其中包含一般不确定的转换率(TRs)。为了解决这一问题,提出了一种基于观测器的自适应FOC控制框架。首先,通过引入自适应增益,自适应弹性观察者可以在不知道全局拓扑信息和tr的情况下观察领导者的状态,同时抵抗随机切换拓扑和DoS攻击的影响。然后,设计了动态输出反馈控制器,保证了FOC的实现。值得注意的是,控制器设计中的包含系数不再与拉普拉斯矩阵绑定,并且可以灵活地预定义以符合特定的任务需求。此外,对于一般不确定的TRs,分别推导了用于估计器增益矩阵和控制器增益矩阵的线性矩阵不等式。最后,通过仿真验证了理论方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Resilient Flexible-Containment Control for Fully Heterogeneous MASs Subject to DoS Attacks and Asynchronous Semi-Markov Chains.

This article investigates the adaptive resilient flexible output containment (FOC) control problem for semi-Markov jump fully heterogeneous multiagent systems (FHMASs) under random switching topologies and denial-of-service (DoS) attacks. In contrast to most existing containment control results, the proposed control strategy can address the challenges posed by the full heterogeneity of multiagent systems (MASs), particularly when multiple leaders exhibit different system dynamics. To better reflect real-world MASs and communication networks, multiple asynchronous semi-Markov chains are employed for the first time to capture system parameter variations and communication topology switching, incorporating generally uncertain transition rates (TRs). In order to deal with this problem, a novel adaptive observer-based FOC control framework is developed. First, by introducing an adaptive gain, the adaptive resilient observers can observe leaders' states without prior knowledge of global topology information and TRs, while resisting the impacts of random switching topologies and DoS attacks. Then, a dynamic output feedback controller is designed to ensure the achievement of FOC. Notably, the containment coefficients in the controller design are no longer tied to the Laplacian matrix and can be flexibly predefined to align with specific task requirements. Furthermore, the linear matrix inequalities (LMIs) to obtain estimator gain matrices and controller gain matrices are derived for the case of generally uncertain TRs, respectively. Finally, the effectiveness of the theoretical method is demonstrated through the simulation.

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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
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.
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