Title
Asymptotical state synchronization for the controlled directed complex dynamic network via links dynamics
Abstract
From the perspective of large-scale system, a directed complex dynamic network (DCDN) may be considered as a coupling system of the node subsystem (NS) and the link subsystem (LS). In this paper, by using the outgoing link vector and incoming link vector for DCDN, the dynamics of LS is described by employing the vector differential equation instead of the matrix differential equation. Since the outgoing and incoming link vectors have the stronger geometric intuition, the results in this paper show that this kind model of links can not only reflect the direction of links but also find the dynamic tracking goal of links more easily when the state synchronization of NS emerges. Furthermore, by employing the simple mathematical conditions, the nonlinear controller of NS and the coupling term of LS are proposed to ensure achieving the asymptotical state synchronization for DCDN. Finally, the numerical simulations are given to demonstrate the validity of the results in this paper.
Year
DOI
Venue
2021
10.1016/j.neucom.2021.03.095
Neurocomputing
Keywords
DocType
Volume
Directed complex dynamic network (DCDN),Node subsystem (NS),Link subsystem (LS),Asymptotical state synchronization,The outgoing and incoming link vectors
Journal
448
ISSN
Citations 
PageRank 
0925-2312
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Peitao Gao100.68
Yinhe Wang2143.58
Lizhi Liu300.34
lili zhang482.46
Xiao Tang500.34