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复杂网络中具有非同质节点的多个非线性耦合动力子网的簇同步。

Cluster Synchronization on Multiple Nonlinearly Coupled Dynamical Subnetworks of Complex Networks With Nonidentical Nodes.

出版信息

IEEE Trans Neural Netw Learn Syst. 2017 Mar;28(3):570-583. doi: 10.1109/TNNLS.2016.2547463. Epub 2016 Apr 15.

Abstract

In this paper, cluster synchronization on multiple nonlinearly coupled dynamical subnetworks of complex networks with nonidentical nodes and stochastic perturbations is studied. Based on the general leader-follower's model, an improved network structure model that consists of multiple pairs of matching subnetworks, each of which includes a leaders' subnetwork and a followers' subnetwork, is proposed. Moreover, the dynamical behaviors of the nodes belonging to the same pair of matching subnetworks are identical, while the ones belonging to different pairs of unmatched subnetworks are nonidentical. In this new setting, the aim is to design some suitable adaptive pinning controllers on the chosen nodes of each followers' subnetwork, such that the nodes in each subnetwork can be exponentially synchronized onto their reference state. Then, some cluster synchronization criteria for multiple nonlinearly coupled dynamical subnetworks of complex networks are established, and a pinning control scheme that the nodes with very large or low degrees are good candidates for applying pinning controllers is presented. Suitable adaptive update laws are used to deal with the unknown feedback gains between the pinned nodes and their leaders. Finally, several numerical simulations are given to demonstrate the effectiveness and applicability of the proposed approach.

摘要

本文研究了具有非同质节点和随机扰动的复杂网络多个非线性耦合子网络上的簇同步问题。基于一般的主从模型,提出了一种由多个匹配子网络对组成的改进网络结构模型,每个匹配子网络对包括一个领导者子网络和一个跟随者子网络。此外,属于同一对匹配子网络的节点的动态行为是相同的,而属于不同的不匹配子网络对的节点的动态行为是不同的。在这种新的设置中,目的是在每个跟随者子网络的选定节点上设计一些合适的自适应钉扎控制器,以使每个子网络中的节点能够指数同步到它们的参考状态。然后,建立了复杂网络多个非线性耦合动力子网络的簇同步判据,并提出了一种节点具有较大或较小度数的钉扎控制方案,适合应用钉扎控制器。采用合适的自适应更新律来处理固定节点与其领导者之间的未知反馈增益。最后,给出了几个数值模拟,以验证所提出方法的有效性和适用性。

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