Pinning Adaptive Passivity and Bipartite Synchronization of Leaderless Fractional Spatiotemporal Networks

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-11 DOI:10.1109/TNSE.2024.3496199

Yu Sun;Cheng Hu;Shipin Wen;Juan Yu;Haijun Jiang

引用次数: 0

Abstract

In this article, by developing a direct error approach, the pinning passivity of leaderless fractional spatiotemporal networks and the leaderless bipartite synchronization of fractional spatiotemporal networks over a signed topological graph are investigated respectively. Above all, a fractional-order edge-based adaptive pinning strategy is designed based on the spanning tree to achieve the passivity of leaderless systems with Dirichlet boundary condition. Next, the fractional spatiotemporal networks with signed graph are discussed and some conditions are obtained to realize leaderless bipartite synchronization based on the derived passivity results and gauge transformation. Note that, the passivity and synchronization of networks are directly investigated without defining any reference state. The developed criteria are eventually verified by several illustrative examples.

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无领导分数时空网络的自适应被动与二部同步

本文通过建立直接误差方法，分别研究了无领导分数时空网络的钉住无源性和分数时空网络在带符号拓扑图上的无领导二部同步性。首先，设计了一种基于生成树的分数阶边自适应固定策略，以实现具有Dirichlet边界条件的无领导系统的无源性。在此基础上，讨论了带符号图的分数时空网络，并根据所导出的无源性结果和规范变换，得到了实现无领导二部同步的条件。注意，在不定义任何参考状态的情况下，直接研究了网络的被动性和同步性。最后通过几个实例验证了所开发的准则。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.