Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/6488
Title: Robust synchronization for 2-D discrete-time coupled dynamical networks
Authors: Liang, J
Wang, Z
Liu, X
Louvieris, P
Keywords: 2-D systems;Complex networks;Coupling;Parameter uncertainties;Synchronization
Issue Date: 2012
Publisher: IEEE
Citation: IEEE Transactions on Neural Networks and Learning Systems, 23(6): 942 - 953, Jun 2012
Abstract: In this paper, a new synchronization problem is addressed for an array of 2-D coupled dynamical networks. The class of systems under investigation is described by the 2-D nonlinear state space model which is oriented from the well-known Fornasini–Marchesini second model. For such a new 2-D complex network model, both the network dynamics and the couplings evolve in two independent directions. A new synchronization concept is put forward to account for the phenomenon that the propagations of all 2-D dynamical networks are synchronized in two directions with influence from the coupling strength. The purpose of the problem addressed is to first derive sufficient conditions ensuring the global synchronization and then extend the obtained results to more general cases where the system matrices contain either the norm-bounded or the polytopic parameter uncertainties. An energy-like quadratic function is developed, together with the intensive use of the Kronecker product, to establish the easy-to-verify conditions under which the addressed 2-D complex network model achieves global synchronization. Finally, a numerical example is given to illustrate the theoretical results and the effectiveness of the proposed synchronization scheme.
Description: This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEE
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6191361
http://bura.brunel.ac.uk/handle/2438/6488
DOI: http://dx.doi.org/10.1109/TNNLS.2012.2193414
ISSN: 2162-237X
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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