Brief Papers
Adaptive pinning control of cluster synchronization in complex
networks with Lurie-type nonlinear dynamics
$
Ling Guo
a,
n
, Huan Pan
b
, Xiaohong Nian
c
a
College of Electrical Engineering, Northwest University for Nationalities, Lanzhou 730030, China
b
College of Physics Electrical Information Engineering, Ningxia University, Yinchuan 750021, China
c
College of Information Science and Engineering, Central South University, Changsha 410075, China
article info
Article history:
Received 20 April 2015
Received in revised form
18 September 2015
Accepted 5 December 2015
Communicated by D. Liu
Available online 22 December 2015
Keywords:
Cluster synchronization
Lurie dynamics network
Adaptive control
Disturbance
Time-varying delay
abstract
In this paper, cluster synchronization problem is investigated for a kind of complex dynamical networks
with Lurie-type non-linear dynamics. With the aid of a local update law, a pinning adaptive control
strategy is proposed to solve the cluster synchronization problem of the networks. Some simple criteria
for cluster synchronization are presented for the networks with external disturbances and time delays.
Firstly, sufficient conditions are established to realize cluster synchronization of the networks without
disturbances and delays. Then, the cluster synchronization problem of the networks with external dis-
turbances is considered. Finally, the cluster synchronization in the networks with time-varying delays is
further studied. Numerical examples are given to verify and illustrate the theoretical results.
& 2015 Elsevier B.V. All rights reserved.
1. Introduction
The collection behaviors of complex dynamics networks have
been received much attention from various areas due to its
important applications in engineering control, social and ecologi-
cal science, etc. As one of the fundamental and significant topics,
synchronization and control have been extensively investigated
during the past few decades. There are various types of synchro-
nization problems that have been developed in the literature such
as complete synchronization, phase synchronization, impulsive
synchronization [1], projective synchronization, generalized syn-
chronization and cluster synchronization, each of which plays an
important role in the study of complex dynamics networks.
Complete synchronization of complex dynamical networks
[2–6] used to study all nodes approaching to a common behavior.
In particular, consensus of multi-agent systems with first-order
dynamics can be regarded as a special case of it [7–11]. Cluster
synchronization [12–21] focuses on when the set of nodes in the
network is divided into several clusters, all individuals in the same
cluster realize synchronization, but there is no synchronization
among different clusters. Cluster synchronization is a common
phenomenon and has its broad potential applications in theore-
tical and engineering aspects. Due to the complicated goals in
practice, the interconnected individuals may evolve into different
subgroups with their own specific goals. Cluster synchronization
can be regarded as an extension of the synchronization problem
and reduces to complete synchronization if all individuals have
only one goal. It can be observed in flocks of birds [22], opinion
formation of social networks [23], and circuits [24]. For instances,
in flocks of bark-foraging birds, the birds will be naturally divided
into communities. When a team of autonomous vehicles is to carry
out a complex task, that can be divided into several simple sub-
task, greater efficiency and operational scheme is realized by the
team of autonomous vehicles dividing into subgroup fashion.
Recently, a variety of control strategies have been presented to
solve cluster synchronization problem. As one of the efficient
strategies in control for complex dynamical networks, pinning
adaptive control has been widely investigated, in which only a
very few fraction of nodes are controlled, and it also provides a
systematic approach for automatic on-line tuning of controller
parameters. Noted that it is economical and effective in large scale
networks. In [12], a cluster synchronization pattern of a general
network was realized by pinning control, and adaptive control
strategy was also introduced. Then, the cluster synchronization
problem for the networks by intermittent pinning control was
further explored in [11]. By using a decentralized adaptive pinning
control strategy, cluster synchronization of undirected complex
dynamical networks was investigated in [14].In[15], the authors
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/neucom
Neurocomputing
http://dx.doi.org/10.1016/j.neucom.2015.12.024
0925-2312/& 2015 Elsevier B.V. All rights reserved.
☆
This work is supported by National Nature Science Foundation of China (Grant
nos. 61463046, 61403219, 61473314, U1134108), and Gansu Province Science
Foundation for Youths (Grant no. 145RJYA282)
n
Corresponding author.
E-mail address: gling0826@126.com (L. Guo).
Neurocomputing 182 (2016) 294–303