Sampled-data synchronization of delayed multi-agent networks and its application to coupled circuit

Nallappan Gunasekaran, Guisheng Zhai, Qiang Yu

Research output: Contribution to journalArticlepeer-review

Abstract

This paper deals with the synchronization control of general chaotic delayed neural networks via sampled-data controllers. The synchronization problem is reduced to a stabilization one, and then a Lyapunov–Krasovskii function (LKF) is proposed to obtain the sufficient condition for the asymptotic stability. Moreover, the sufficient condition is presented by linear matrix inequalities (LMIs), which are easy to solve by existing software. Three numerical examples including electrical circuits are provided to confirm validity of the theoretical results.

Original languageEnglish
Pages (from-to)499-511
Number of pages13
JournalNeurocomputing
Volume413
DOIs
Publication statusPublished - 2020 Nov 6

Keywords

  • Linear matrix inequality (LMI)
  • Lyapunov method
  • Multi-agent networks
  • Synchronization
  • Time-delay

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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