Event-triggered sliding mode control for interval type-2 fuzzy interconnected systems under Markov-model-based hybrid cyberattacks

IF 6.8 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Xiulin Wang , Feng Li , Sangmoon Lee , Hao Shen
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引用次数: 0

Abstract

This paper studies the event-triggered sliding mode control problem for interval type-2 fuzzy interconnected systems under hybrid cyberattacks modeled by Markov processes. Under the framework of an interval type-2 fuzzy model, the nonlinear relationship in the interconnected system is modeled and analyzed, and a fuzzy sliding mode controller is designed which can effectively resist hybrid cyberattacks. To rationally utilize limited channel resources, a decentralized event-triggered mechanism is used to reduce unnecessary information transmission. By constructing a Lyapunov function, some criteria are deduced to ensure that the closed-loop system is stochastically passive and the reachability of the designed sliding area is guaranteed. Finally, a four-area networked interconnected system is used to verify the effectiveness of the decentralized fuzzy sliding mode control strategy.
马尔可夫混合网络攻击下区间2型模糊互联系统的事件触发滑模控制
研究了区间2型模糊互联系统在马尔可夫过程混合网络攻击下的事件触发滑模控制问题。在区间2型模糊模型框架下,对互联系统的非线性关系进行建模和分析,设计了能有效抵抗混合网络攻击的模糊滑模控制器。为了合理利用有限的信道资源,采用去中心化的事件触发机制,减少不必要的信息传输。通过构造Lyapunov函数,推导出保证闭环系统随机无源性和设计滑动区域可达性的准则。最后,通过一个四区域联网互联系统,验证了分散模糊滑模控制策略的有效性。
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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