Nonfragile Exponential Synchronization of Delayed Complex Dynamical Networks with Memory Sampled-Data Control

Yajuan Liu, Bao Zhu Guo, Ju H. Park, Sang Moon Lee

Research output: Contribution to journalArticlepeer-review

207 Scopus citations

Abstract

This paper considers nonfragile exponential synchronization for complex dynamical networks (CDNs) with time-varying coupling delay. The sampled-data feedback control, which is assumed to allow norm-bounded uncertainty and involves a constant signal transmission delay, is constructed for the first time in this paper. By constructing a suitable augmented Lyapunov function, and with the help of introduced integral inequalities and employing the convex combination technique, a sufficient condition is developed, such that the nonfragile exponential stability of the error system is guaranteed. As a result, for the case of sampled-data control free of norm-bound uncertainties, some sufficient conditions of sampled-data synchronization criteria for the CDNs with time-varying coupling delay are presented. As the formulations are in the framework of linear matrix inequality, these conditions can be easily solved and implemented. Two illustrative examples are presented to demonstrate the effectiveness and merits of the proposed feedback control.

Original languageEnglish
Article number7636934
Pages (from-to)118-128
Number of pages11
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume29
Issue number1
DOIs
StatePublished - Jan 2018

Keywords

  • Complex dynamical networks (CDNs)
  • memory sampled-data control
  • nonfragile synchronization
  • time-varying coupling delay

Fingerprint

Dive into the research topics of 'Nonfragile Exponential Synchronization of Delayed Complex Dynamical Networks with Memory Sampled-Data Control'. Together they form a unique fingerprint.

Cite this