Literature DB >> 25797504

Stochastic sampled-data control for synchronization of complex dynamical networks with control packet loss and additive time-varying delays.

R Rakkiyappan1, N Sakthivel1, Jinde Cao2.   

Abstract

This study examines the exponential synchronization of complex dynamical networks with control packet loss and additive time-varying delays. Additionally, sampled-data controller with time-varying sampling period is considered and is assumed to switch between m different values in a random way with given probability. Then, a novel Lyapunov-Krasovskii functional (LKF) with triple integral terms is constructed and by using Jensen's inequality and reciprocally convex approach, sufficient conditions under which the dynamical network is exponentially mean-square stable are derived. When applying Jensen's inequality to partition double integral terms in the derivation of linear matrix inequality (LMI) conditions, a new kind of linear combination of positive functions weighted by the inverses of squared convex parameters appears. In order to handle such a combination, an effective method is introduced by extending the lower bound lemma. To design the sampled-data controller, the synchronization error system is represented as a switched system. Based on the derived LMI conditions and average dwell-time method, sufficient conditions for the synchronization of switched error system are derived in terms of LMIs. Finally, numerical example is employed to show the effectiveness of the proposed methods.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Keywords:  Additive time-varying delays; Complex dynamical networks; Control packet loss; Reciprocally convex approach; Stochastic sampled-data

Mesh:

Year:  2015        PMID: 25797504     DOI: 10.1016/j.neunet.2015.02.011

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  3 in total

1.  New delay-interval-dependent stability criteria for switched Hopfield neural networks of neutral type with successive time-varying delay components.

Authors:  R Manivannan; R Samidurai; Jinde Cao; Ahmed Alsaedi
Journal:  Cogn Neurodyn       Date:  2016-07-19       Impact factor: 5.082

2.  A New Model for Complex Dynamical Networks Considering Random Data Loss.

Authors:  Xu Wu; Guo-Ping Jiang; Xinwei Wang
Journal:  Entropy (Basel)       Date:  2019-08-15       Impact factor: 2.524

3.  Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems.

Authors:  Vandana Sakhre; Sanjeev Jain; Vilas S Sapkal; Dev P Agarwal
Journal:  Comput Intell Neurosci       Date:  2015-08-20
  3 in total

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