Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays

doi:10.1088/1674-1056/21/4/048402

Abstract Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov-Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method.

Keywords: asymptotic stability chaos fuzzy cellular neural networks linear matrix inequalities synchronization

Received: 26 August 2011
Revised: 30 August 2011
Accepted manuscript online:

PACS:	84.35.+i	(Neural networks)
	05.45.Gg	(Control of chaos, applications of chaos)
	05.45.Xt	(Synchronization; coupled oscillators)
	07.05.Mh	(Neural networks, fuzzy logic, artificial intelligence)

Fund: Project supported by No. DST/INSPIRE Fellowship/2010/[293]/dt. 18/03/2011.

Corresponding Authors: P. Balasubramaniam,balugru@gmail.com
E-mail: balugru@gmail.com

Cite this article:

P. Balasubramaniam, M. Kalpana, and R. Rakkiyappan Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays 2012 Chin. Phys. B 21 048402

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Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays

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