Neural network H∞ chaos synchronization

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

This paper proposes a new neural network H∞ synchronization (NNHS) scheme for unknown chaotic systems. In the proposed framework, a dynamic neural network is constructed as an alternative to approximate the chaotic system. Based on this neural network and linear matrix inequality (LMI) formulation, the NNHS controller and the learning law are presented to reduce the effect of disturbance to an H∞ norm constraint. It is shown that finding the NNHS controller and the learning law can be transformed into the LMI problem and solved using the convex optimization method. A numerical example is presented to demonstrate the validity of the proposed NNHS scheme.

Original languageEnglish
Pages (from-to)295-302
Number of pages8
JournalNonlinear Dynamics
Volume60
Issue number3
DOIs
Publication statusPublished - 2010 May

Keywords

  • Dynamic neural networks
  • H∞ synchronization
  • Linear matrix inequality (LMI)
  • Unknown chaotic systems
  • Weight learning law

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering
  • Applied Mathematics
  • Electrical and Electronic Engineering

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