Delay-dependent H control for discrete-time uncertain recurrent neural networks with intrerval time-varying delay

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This paper deals with the problem of delay-dependent robust H control for discrete-time recurrent neural networks (DRNNs) with norm-bounded parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. For the robust stabilization problem, a state feedback controller is designed to ensure global robust stability of the closed-loop system about its equilibrium point for all admissible uncertainties, while for the robust H control problem, attention is focused on the design of a state feedback controller such that in addition to the requirement of the global robust stability, a prescribed H performance level for all delays to satisfy both the lower bound and upper bound of the interval time-varying delay is also required to be achieved. A linear matrix inequality approach is developed to solve these problems. It is shown that the desired state feedback controller can be constructed by solving certain LMIs. A numerical example is provided to demonstrate the effectiveness and applicability of the proposed results. ICIC International

Original languageEnglish
Pages (from-to)3483-3493
Number of pages11
JournalInternational Journal of Innovative Computing, Information and Control
Issue number10
Publication statusPublished - 2009 Oct 1


All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Computational Theory and Mathematics

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