Asynchronous Control for Interval Type-2 Fuzzy Nonhomogeneous Markov Jump Systems Against Successive DoS Attacks

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-10-25 DOI:10.1109/TCYB.2024.3476426
Min Xue;James Lam;Huaicheng Yan;Ka-Wai Kwok
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Abstract

This article is concerned with the problem of asynchronous control for Interval Type-2 (IT2) fuzzy nonhomogeneous Markov jump systems against successive denial-of-service (DoS) attacks. The system and the controller are assumed to be connected through a communication channel subject to malicious attacks. The maximum number and probability distribution of successive attacks are considered. Under the imperfect premise matching, a fuzzy asynchronous controller is constructed by the hidden Markov model. By means of the introduced transmission delay, a delay closed-loop system is constructed, where the stochastic description of the delay depends on the statistical characteristic of successive attacks. Then stability criteria together are derived in the form of linear matrix inequalities by the Lyapunov functional approach, as well as the condition on the existence of the fuzzy controller. Finally, the feasibility and effectiveness of the presented control scheme are demonstrated by simulation results.
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针对连续 DoS 攻击的间隔型-2 模糊非均质马尔可夫跃迁系统的异步控制
研究了区间2型(IT2)模糊非齐次马尔可夫跳变系统在连续拒绝服务攻击下的异步控制问题。假设系统和控制器通过一个容易受到恶意攻击的通信通道连接。考虑了连续攻击的最大次数和概率分布。在不完全前提匹配下,利用隐马尔可夫模型构造了模糊异步控制器。利用引入的传输时延,构造了一个时延闭环系统,其中时延的随机描述依赖于连续攻击的统计特征。然后利用Lyapunov泛函方法以线性矩阵不等式的形式导出了系统的稳定性判据,并给出了模糊控制器存在的条件。最后,通过仿真结果验证了所提控制方案的可行性和有效性。
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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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