ARTICLE IN PRESS
JID: NEUCOM [m5G; May 25, 2017;21:47 ]
Neurocomputing 0 0 0 (2017) 1–8
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Neurocomputing
journal homepage: www.elsevier.com/locate/neucom
Adaptive finite-time control for overlapping cluster synchronization in
coupled complex networks
Shengqin Jiang
a , b
, Xiaobo Lu
a , b , ∗
, Chao Xie
a , b
, Shuiming Cai
c
a
School of Automation, Southeast University, Nanjing 210096, China
b
Key Laboratory of Measurement and Control of Complex Systems of Engineering , Ministry of Education, Nanjing 210096, China
c
Faculty of Science, Jiangsu University, Zhenjiang, Jiangsu 212013, China
a r t i c l e i n f o
Article history:
Received 9 January 2017
Revised 8 March 2017
Accepted 15 May 2017
Available online xxx
Communicated by Sakthivel Rathinasamy
Keywords:
Adaptive control
Finite time control
Overlapping cluster
Coupled complex networks
a b s t r a c t
In this paper, we address the overlapping cluster synchronization problem of coupled complex networks
via adaptive finite-time control. Cluster synchronization indeed has been extensively addressed by vari-
ous control strategies. The communities in the cluster-based networks always do not share nodes with
each other but exchange messages. Then, according to natural community, we propose a new overlap-
ping community model for the coupled complex network to remove the restriction on common commu-
nity models. The community in our model contains two kinds of nodes: overlapped and non-overlapped
nodes, which is different from the common cluster form explored in the synchronization processing. In
addition, a new control strategy is expressly proposed to extract every inner cluster in the overlapped re-
gions. Especially, a novel adaptive finite-time control strategy is also proposed to force every community
to a desired trajectory in finite time. On the basis of finite time theory, sufficient cluster synchronization
criteria are derived. Lastly, the effectiveness of analytical results is confirmed by a numerical example.
©2017 Elsevier B.V. All rights reserved.
1. Introduction
Many complex systems are significant and vital to human life,
society and governance, and can be described in terms of complex
networks [1–3] . Hitherto, the properties or function of complex
networks have been extensively investigated in the fields of en-
gineering, physics, biology, chemistry, and computer science [4–9] .
Therein synchronization, an important part in the analysis of net-
work dynamics, has attracted much attention due to the important
applications in secure communication, image processing, platoon-
ing of vehicles and cooperation of robotic systems [4,5,7] . With
the development in this direction, many different kinds of synchro-
nization protocols have been investigated, e.g., complete synchro-
nization, projective synchronization and cluster synchronization.
Cluster synchronization in recent years has received great at-
tention which is equally important and more ordinary compared to
other synchronous patterns as reported in [9] . This is mostly given
to the following facts: the topological structure of many practi-
cal networks often features an organization of communities, e.g.,
social networks and biological networks, the nodes in the same
∗
Corresponding author at: School of Automation, Southeast University, Nanjing
210096, China
E-mail address: xblu2013@126.com (X. Lu).
cluster have the same function or property [10] , and this research
is of significance in biological sciences and communication engi-
neering [11] . To date, several noticeable results have been obtained
[7,11–15] . In [12] , Yang et al. achieved finite-time cluster synchro-
nization of T-S fuzzy complex networks by finite-time control tech-
nique. In [13] , Lee et al. designed a pinning controller for cluster
synchronization of complex dynamical networks with semi-
Markovian jump topology. More recently, the authors in [14] ad-
dressed the cluster synchronization problem for nonlinearly
time-varying delayed coupling complex networks with stochastic
perturbation.
Most cluster synchronization methods regard the complex net-
works as a set of communities which are often independent of
each other, i.e., a node only belongs to a fixed community. How-
ever, most real networks are characterized by well-defined statis-
tics of overlapped and nested communities [3,10] , for example, in
social network, a person may belong to two or more communi-
ties. Consequently, it is also of importance to consider the synchro-
nization of overlapping networks which helps us to understand the
dynamics of the networks, especially the nodes in the overlapped
regions. So far, a great deal of work has concentrated on the syn-
chronization problems or other dynamics of overlapping complex
networks [10,15–18] . In [16] , Li et al. reported that a complex net-
work of phase oscillators may display interfaces between clusters
of synchronized oscillations. In [17] , the authors proposed a simple
http://dx.doi.org/10.1016/j.neucom.2017.05.031
0925-2312/© 2017 Elsevier B.V. All rights reserved.
Please cite this article as: S. Jiang et al., Adaptive finite-time control for overlapping cluster synchronization in coupled complex net-
works, Neurocomputing (2017), http://dx.doi.org/10.1016/j.neucom.2017.05.031