干扰和DoS攻击下多智能体系统的鲁棒量化一致性

IF 5 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Xinhe Wang;Guanghui Wen;Dan Zhao;Tingwen Huang
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引用次数: 0

摘要

外部干扰和拒绝服务(DoS)攻击对多智能体系统(MASs)的量化控制提出了重大挑战。现有的量化控制策略大多侧重于设计标度因子和构建辅助系统,而不考虑外部干扰。注意,这些策略需要高度精确的系统模型,如果存在外部干扰,将导致量化器饱和。为了克服上述缺点,本文开发了一种新的标度函数,将鲁棒性因素纳入标度函数设计中,显著提高了量化机制的鲁棒性。在此基础上,设计了一种鲁棒量化控制策略,在存在干扰和DoS攻击的情况下实现线性质量的有界共识,并探讨了量化水平、共识性能和对DoS攻击的弹性之间的权衡。此外,鲁棒设计框架在解决DoS攻击下的非线性质量弹性控制方面显示出显著的灵活性和效率。数值模拟验证了理论结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Quantized Consensus of Multiagent Systems Under Disturbance and DoS Attacks
External disturbances and denial-of-service (DoS) attacks pose significant challenges to the quantized control of multiagent systems (MASs). Most of the existing quantized control strategies primarily focus on designing scaling factors and constructing auxiliary systems without considering external disturbances. Note that these strategies require a highly accurate system model and will lead to the saturation of the quantizer if there exist external disturbances. To overcome the aforementioned shortcomings, a new scaling function is developed in this article by incorporating robustness factors into the scaling function design, significantly enhancing the robustness of the quantization mechanism. Based on this, a robust quantized control strategy is designed to achieve the bounded consensus of linear MASs in the presence of disturbance and DoS attacks, where the tradeoff among quantization level, consensus performance, and resilience to DoS attacks is explored. Besides, the robust design framework shows significant flexibility and efficiency in addressing the resilient control of nonlinear MASs subject to DoS attacks. Numerical simulations are provided to validate the theoretical results.
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来源期刊
IEEE Transactions on Control of Network Systems
IEEE Transactions on Control of Network Systems Mathematics-Control and Optimization
CiteScore
7.80
自引率
7.10%
发文量
169
期刊介绍: The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.
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