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Input-to-state stability of stochastic complex networks based on aperiodically intermittent sampled control

  • Tianrui Chen*
  • , Jiacai Chen
  • *Corresponding author for this work
  • Harbin Institute of Technology Weihai

Research output: Contribution to journalArticlepeer-review

Abstract

This paper focuses on the problem of input-to-state stability (ISS) of stochastic complex networks (SCNs). In this paper, an aperiodically intermittent control strategy based on sampled control is designed. By means of graph theory and Lyapunov method, two stability criteria on ISS are derived in this paper. After giving the estimate between E∑i=1m|xi(t)−xi(δ(t))|2 and E∑i=1m|xi(t)|2, a stability criterion is proposed on ISS of the SCN under aperiodically intermittent sampled control (AISC). When AISC degenerates into sampled control, another stability criterion on ISS of SCN is acquired. Finally, a numerical example is utilized to illustrate the effectiveness and feasibility of the proposed results.

Original languageEnglish
Article number127100
JournalNeurocomputing
Volume570
DOIs
StatePublished - 14 Feb 2024
Externally publishedYes

Keywords

  • Aperiodically intermittent control
  • Input-to-state stability
  • Lyapunov method
  • Sampled control
  • Stochastic complex networks

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