Synchronization of continuous dynamical networks with discrete-time communications.

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-10-25 DOI:10.1109/TNN.2011.2171501
Yan-Wu Wang, Jiang-Wen Xiao, Changyun Wen, Zhi-Hong Guan
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引用次数: 52

Abstract

In this paper, synchronization of continuous dynamical networks with discrete-time communications is studied. Though the dynamical behavior of each node is continuous-time, the communications between every two different nodes are discrete-time, i.e., they are active only at some discrete time instants. Moreover, the communication intervals between every two communication instants can be uncertain and variable. By choosing a piecewise Lyapunov-Krasovskii functional to govern the characteristics of the discrete communication instants and by utilizing a convex combination technique, a synchronization criterion is derived in terms of linear matrix inequalities with an upper bound for the communication intervals obtained. The results extend and improve upon earlier work. Simulation results show the effectiveness of the proposed communication scheme. Some relationships between the allowable upper bound of communication intervals and the coupling strength of the network are illustrated through simulations on a fully connected network, a star-like network, and a nearest neighbor network.

离散时间通信连续动态网络的同步。
研究了具有离散时间通信的连续动态网络的同步问题。虽然每个节点的动态行为是连续时间的,但每两个不同节点之间的通信是离散时间的,即它们只在某些离散的时间瞬间是活动的。此外,每两个通信瞬间之间的通信间隔可能是不确定的和可变的。通过选择分段Lyapunov-Krasovskii泛函来控制离散通信瞬间的特征,并利用凸组合技术,导出了基于线性矩阵不等式的同步准则,该准则具有所获得的通信区间的上界。结果扩展和改进了早期的工作。仿真结果表明了该通信方案的有效性。通过对全连通网络、星形网络和最近邻网络的仿真,说明了通信间隔允许上界与网络耦合强度之间的关系。
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来源期刊
IEEE transactions on neural networks
IEEE transactions on neural networks 工程技术-工程:电子与电气
自引率
0.00%
发文量
2
审稿时长
8.7 months
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