Robust Fault Detection during the Synchronization Process of Nonlinear Lur'e Dynamical Networks

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Abstract:

The present study focuses on the robust fault detection issue within the synchronization process of nonlinear Lur'e dynamical networks. Sufficient conditions in terms of linear matrix inequalities (LMIs) are established to guarantee global robust synchronization of the network. Under such a synchronization scheme, the error dynamical system is globally asymptotically stable, the effect of external disturbances is suppressed, and at the same time, the network is sensitive to possible faults based on a mixedperformance.

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Advanced Materials Research (Volumes 718-720)

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1408-1415

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July 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] X. Liu, J.Z. Wang, and L.Huang, Global synchronization for a class of dynamical complex networks,Physica A, 386 (2007) 543-556.

Google Scholar

[2] X. Liu, J.Z. Wang, and L.Huang, Stabilization of a class of dynamical complex networks based ondecentralized control, Physica A, 383 (2007) 733-744.

DOI: 10.1016/j.physa.2007.05.030

Google Scholar

[3] S.Y. Xu and Y. Yang, Synchronization for a class of complex dynamical networks with time-delay,Commun. Nonlinear Sci. Numer.Simulat. 14 (2009) 3230-3238.

DOI: 10.1016/j.cnsns.2008.12.022

Google Scholar

[4] L.O. Chua, Chuas circuit: an overview ten years later, J. Circuits Syst. Comput. 4 (1994) 117-159.

Google Scholar

[5] P. Ruoff, M. Vinsjevik, C. Monnerjahnsjevik, L. Rensing L, The Goodwin model: simulating theeffect of light pulses on the circadian sporulation rhythm of neurosporacrassa, J. Theor. Biol. 209(2001) 29-42.

DOI: 10.1006/jtbi.2000.2239

Google Scholar

[6] V. Gazi, K.M. Passino, Stability analysis of swarms, IEEE Trans. Autom. Control 48 (2003) 692-697.

DOI: 10.1109/tac.2003.809765

Google Scholar

[7] M. Vidyasagar, Nonlinear Systems Analysis, NJ:Prentice-Hall; 1993.

Google Scholar

[8] J. Chen and R.J. Patton, Robust model-based fault diagnosis for dynamic systems, Kluwer AcademicPublishers, Boston, 1999.

Google Scholar

[9] S.X. Ding, Model-based fault diagnosis techniques, design schemes, algorithms, and tools, Springer-Verlag Berlin Heidelberg, 2008.

Google Scholar

[10] J.L. Wang, G.H. Yang and J. Liu, An LMI approach to H∞ index and mixed H−/H∞ fault detectionobserver design, Automatica, 43 (2007) 1656-1665.

Google Scholar

[11] X.B. Li, K.M. Zhou, A time domain approach to robust fault detection of linear time-varying systems,Automatica, 45 (2009) 94-102.

DOI: 10.1016/j.automatica.2008.07.017

Google Scholar

[12] S.Y. Xu, Y. Yang, X. Liu, Y. Tang and H.D. Sun, Robust fault-sensitive synchronization of the Chua's Circuit, Chinese Physics B, 20(2) (2011) 020509.

DOI: 10.1088/1674-1056/20/2/020509

Google Scholar

[13] S. Boyd, L. ELGhaoui, E. Feron, V. Balakrishnam, Linear Matrix Inequalities in Systems andControl, SIMA, Philadelphia, 1994.

Google Scholar

[14] C.W. Wu, Application of kronecker products to the analysis of systems with uniform linear coupling,IEEE Trans. CAS-I, 42(10) (1995) 775-778.

DOI: 10.1109/81.473586

Google Scholar

[15] R.N. Mandan, Chua's Circuit: A Paradigm for Chaos, World Scientific, Singapore, 1993.

Google Scholar