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Author:

Zhang, X. (Zhang, X..) | Luo, B. (Luo, B..) | Wang, Z.-P. (Wang, Z.-P..) | Xu, X. (Xu, X..) | Yang, C. (Yang, C..)

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Scopus

Abstract:

This article addresses the synchronization problem of reaction-diffusion neural networks (RDNNs) with random time-varying delay (RTVD) via boundary control (BC) (including adaptive BC and BC with constant-valued gain) under distributed measurements or boundary measurements. First, a novel BC strategy with constant-valued gain is designed, which considers three cases of the measurements, that is, distributed measurements, boundary measurements, and both coexist. Subsequently, an adaptive BC scheme under boundary measurements is proposed, where the control gain is regulated effectively. Next, based on the inequality techniques and Lyapunov direct approach, the delay-dependent synchronization conditions are gained and some linear matrix inequalities (LMIs) based theorems are given. Then, the BC design for the delayed RDNNs is transformed into an LMI feasibility problem. Finally, the developed BC approaches are validated by the simulation results.  © 2012 IEEE.

Keyword:

random time-varying delay (RTVD) Boundary control (BC) linear matrix inequality (LMI) synchronization reactiona-diffusion neural networks (RDNNs)

Author Community:

  • [ 1 ] [Zhang X.]Central South University, School of Automation, Changsha, 410083, China
  • [ 2 ] [Luo B.]Central South University, School of Automation, Changsha, 410083, China
  • [ 3 ] [Wang Z.-P.]Beijing University of Technology, School of Information Science and Technology, Beijing Laboratory of Smart Environmental Protection, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing Institute of Artificial Intelligence, Beijing, 100124, China
  • [ 4 ] [Xu X.]Central South University, School of Automation, Changsha, 410083, China
  • [ 5 ] [Yang C.]Central South University, School of Automation, Changsha, 410083, China

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Source :

IEEE Transactions on Neural Networks and Learning Systems

ISSN: 2162-237X

Year: 2025

1 0 . 4 0 0

JCR@2022

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 5

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