基于观测器的多通道网络系统异步稳定及其应用。

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Wenhai Qi,Zhenhao Li,Ju H Park,Huaicheng Yan,Zheng-Guang Wu
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引用次数: 0

摘要

在本研究中,针对多通道攻击下的NS,研究了基于观测器的异步镇定问题,其中的异步现象是指控制器模式与实际攻击模式不匹配。为了准确地描述复杂的攻击行为,引入了一种由上层马尔可夫链调制的分段齐次半马尔可夫链(SMC)模型,该模型可以同时描述攻击模式转移的随机性和转移概率的时变性质。考虑到实际攻击模式不可访问,设计了一种基于观测器的模式切换延迟技术来解决这一难题。在分段齐次SMC框架下,利用Lyapunov函数,根据观察到的攻击模式、分段齐次变量和ET,建立了保证随机多通道DoS攻击下误差均方稳定性的充分准则,并采用矩阵解耦和凸化技术降低了计算复杂度。最后,通过两个实际仿真案例验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Observer-Based Asynchronous Stabilization for Networked Systems With Multichannel Attacks and Applications.
In this study, the observer-based asynchronous stabilization is addressed for NS under multichannel attacks, in which the asynchronous phenomenon refers to the mismatch between the controller mode and the actual attack mode. To accurately depict complex attack behaviors, a piecewise homogeneous semi-Markov chain (SMC) model modulated by a superstratum Markov chain is introduced, which can simultaneously describe the randomness of attack mode transitions and the time-varying nature of transition probabilities. Considering that the actual attack modes are inaccessible, an observer-based mode switching delay technique is designed to solve this challenge. Under the framework of a piecewise homogeneous SMC, a sufficient criterion is established to ensure the ς-error mean-square stability under random multichannel DoS attacks by means of a Lyapunov function depending on observed attack modes, piecewise homogeneous variables, and ET. Moreover, matrix decoupling and convexification techniques are employed to reduce the computational complexity. Finally, the effectiveness of the proposed method is demonstrated through two practical simulation cases.
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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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