动态事件触发机制下基于加解密的二维系统有界过滤

IF 6.7 2区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY
Pan Zhang;Chaoqun Zhu;Bin Yang;Bohan Zhang;Zhiwen Wang
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引用次数: 0

摘要

研究了具有加解密机制(EDM)和动态事件触发机制(ETM)的二维离散系统的有界滤波问题。首先,考虑到可能存在的信息泄露问题,设计了一种基于量化编解码机制的二维系统电火花加工方案。此外,提出了具有双向进化特征的动态ETM,以减轻计算和通信负担。在该框架下,分别得到了窃听端和用户端的滤波误差系统(FESs)。随后,设计加密参数,使窃听方的过滤误差发散。此外,建立了有界性准则,以确保客户端FESs在Lyapunov稳定性分析方法方面是有界的。最后,证明了所提出的有界滤波算法对几种工业环境下的二维系统是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Encryption-Decryption-Based Bounded Filtering for 2-D Systems Under Dynamic Event-Triggered Mechanism
This paper investigates the bounded filtering problem for two-dimensional (2-D) discrete systems with encryption-decryption mechanism (EDM) and dynamic event-triggered mechanism (ETM). Firstly, considering the potential information leakage, a novel EDM is designed for 2-D systems based on the quantization-based encoding-decoding mechanism. In addition, the dynamic ETM with bidirectional evolutionary characteristics is proposed to alleviate the computational and communication burdens. In such a framework, the filtering error systems (FESs) at the eavesdropper side and the user side are obtained, respectively. Subsequently, the encryption parameters are devised such that the filtering error at the eavesdropper side diverges. Additionally, the boundedness criteria are established to ensure that the client-side FESs are bounded in terms of Lyapunov stability analysis approach. Finally, it is demonstrated that the proposed bounded filtering algorithm is valid for 2-D systems in several types of industrial environments.
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来源期刊
IEEE Transactions on Network Science and Engineering
IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering
CiteScore
12.60
自引率
9.10%
发文量
393
期刊介绍: The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.
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