Prescribed-time stabilization of stochastic complex dynamical networks with aperiodically intermittent pinning control
Ying Guo,
Xiaotong Liu,
Xue Long and
Junning Zhang
Chaos, Solitons & Fractals, 2025, vol. 196, issue C
Abstract:
In this paper, a new type of aperiodically intermittent pinning control (AIPC) is proposed to investigate the prescribed-time stabilization (PTS) of stochastic complex dynamical networks (SCDNs). It is worth noting that the paper provides a theorem for realizing PTS for SCDNs under AIPC and affords a corollary of the relationship between the state of the nodes of the SCDNs and the control gain of AIPC. Besides, using the Lyapunov method and graph theory, SCDNs under AIPC can reach PTS at the given settling time, when only some of the nodes of SCDNs need to be controlled during the aperiodically intermittent control time. Compared to the existing literature, the AIPC in this paper no longer emphasizes that SCDNs must be strongly connected, but simply need to be connected. Furthermore, the theoretical results are employed to Chua’s chaotic circuits and a numerical simulation is offered to support the validity of the theoretical results.
Keywords: Prescribed-time stabilization; Aperiodically intermittent control; Pinning control; Stochastic complex dynamical networks (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077925003546
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:196:y:2025:i:c:s0960077925003546
DOI: 10.1016/j.chaos.2025.116341
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().