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

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 th...

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Veröffentlicht in:Neurocomputing (Amsterdam) 2024-02, Vol.570, p.127100, Article 127100
Hauptverfasser: Chen, Tianrui, Chen, Jiacai
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2023.127100