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Sliding mode control for uncertain fractional-order reaction–diffusion memristor neural networks with time delays

  • Yue Cao
  • , Yonggui Kao*
  • , Zhen Wang
  • , Xinsong Yang
  • , Ju H. Park
  • , Wei Xie
  • *Corresponding author for this work
  • Harbin Institute of Technology Weihai
  • Shandong University of Science and Technology
  • Sichuan University
  • Yeungnam University
  • School of Information Science and Engineering, Harbin Institute of Technology Weihai

Research output: Contribution to journalArticlepeer-review

Abstract

This paper investigates a sliding mode control method for a class of uncertain delayed fractional-order reaction–diffusion memristor neural networks. Different from most existing literature on sliding mode control for fractional-order reaction–diffusion systems, this study constructs a linear sliding mode switching function and designs the corresponding sliding mode control law. The sufficient theory for the globally asymptotic stability of the sliding mode dynamics are provided, and it is proven that the sliding mode surface is finite-time reachable under the proposed control law, with an estimate of the maximum reaching time. Finally, a numerical test is presented to validate the effectiveness of the theoretical analysis.

Original languageEnglish
Article number106402
JournalNeural Networks
Volume178
DOIs
StatePublished - Oct 2024
Externally publishedYes

Keywords

  • Fractional-order
  • Memristor neural networks
  • Reaction–diffusion
  • Sliding mode control
  • Time delays

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