基于采样数据控制的时间平方相关环函数耦合延迟复杂动态网络同步

IF 6.5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Haripriya Muralikrishnan , N. Padmaja , E. Umamaheswari , Lakshmanan Shanmugam
{"title":"基于采样数据控制的时间平方相关环函数耦合延迟复杂动态网络同步","authors":"Haripriya Muralikrishnan ,&nbsp;N. Padmaja ,&nbsp;E. Umamaheswari ,&nbsp;Lakshmanan Shanmugam","doi":"10.1016/j.neucom.2025.130819","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes a novel sampled-data control (SDC) approach for addressing synchronization problems in complex dynamical networks (CDNs) with coupling delays in time-square-dependent looped-functionals (TSDLFs). The proposed method introduces a sampling-time-dependent control signal to achieve synchronization while considering coupled time-varying delays and uncertainties in CDNs. To ensure asymptotic stability, new Lyapunov functionals are constructed, including TSDLFs and two-sided looped functionals, effectively utilizing information over the intervals <span><math><mrow><mo>[</mo><msub><mrow><mstyle><mi>t</mi></mstyle></mrow><mrow><mi>k</mi></mrow></msub><mo>,</mo><mstyle><mi>t</mi></mstyle><mo>]</mo></mrow></math></span> and <span><math><mrow><mo>[</mo><mstyle><mi>t</mi></mstyle><mo>,</mo><msub><mrow><mstyle><mi>t</mi></mstyle></mrow><mrow><mi>k</mi><mo>+</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></math></span>. Sufficient conditions are derived to guarantee the asymptotic stability of the error states. A numerical example based on Chua’s circuits demonstrates the effectiveness and superiority of the proposed method.</div></div>","PeriodicalId":19268,"journal":{"name":"Neurocomputing","volume":"649 ","pages":"Article 130819"},"PeriodicalIF":6.5000,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Synchronization for coupling delayed complex dynamical networks in time-square-dependent looped-functionals via a new sampled-data control approach\",\"authors\":\"Haripriya Muralikrishnan ,&nbsp;N. Padmaja ,&nbsp;E. Umamaheswari ,&nbsp;Lakshmanan Shanmugam\",\"doi\":\"10.1016/j.neucom.2025.130819\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper proposes a novel sampled-data control (SDC) approach for addressing synchronization problems in complex dynamical networks (CDNs) with coupling delays in time-square-dependent looped-functionals (TSDLFs). The proposed method introduces a sampling-time-dependent control signal to achieve synchronization while considering coupled time-varying delays and uncertainties in CDNs. To ensure asymptotic stability, new Lyapunov functionals are constructed, including TSDLFs and two-sided looped functionals, effectively utilizing information over the intervals <span><math><mrow><mo>[</mo><msub><mrow><mstyle><mi>t</mi></mstyle></mrow><mrow><mi>k</mi></mrow></msub><mo>,</mo><mstyle><mi>t</mi></mstyle><mo>]</mo></mrow></math></span> and <span><math><mrow><mo>[</mo><mstyle><mi>t</mi></mstyle><mo>,</mo><msub><mrow><mstyle><mi>t</mi></mstyle></mrow><mrow><mi>k</mi><mo>+</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></math></span>. Sufficient conditions are derived to guarantee the asymptotic stability of the error states. A numerical example based on Chua’s circuits demonstrates the effectiveness and superiority of the proposed method.</div></div>\",\"PeriodicalId\":19268,\"journal\":{\"name\":\"Neurocomputing\",\"volume\":\"649 \",\"pages\":\"Article 130819\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2025-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurocomputing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0925231225014912\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurocomputing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0925231225014912","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种新的采样数据控制(SDC)方法,用于解决具有时间平方相关环函数(tsdlf)耦合延迟的复杂动态网络(cdn)中的同步问题。该方法引入了一个采样时变控制信号来实现同步,同时考虑了cdn中的耦合时变延迟和不确定性。为了保证渐近稳定性,构造了新的Lyapunov泛函,包括tsdlf和双面环泛函,有效地利用了区间[tk,t]和[t,tk+1]上的信息。给出了保证误差状态渐近稳定的充分条件。基于蔡氏电路的数值算例验证了该方法的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synchronization for coupling delayed complex dynamical networks in time-square-dependent looped-functionals via a new sampled-data control approach
This paper proposes a novel sampled-data control (SDC) approach for addressing synchronization problems in complex dynamical networks (CDNs) with coupling delays in time-square-dependent looped-functionals (TSDLFs). The proposed method introduces a sampling-time-dependent control signal to achieve synchronization while considering coupled time-varying delays and uncertainties in CDNs. To ensure asymptotic stability, new Lyapunov functionals are constructed, including TSDLFs and two-sided looped functionals, effectively utilizing information over the intervals [tk,t] and [t,tk+1). Sufficient conditions are derived to guarantee the asymptotic stability of the error states. A numerical example based on Chua’s circuits demonstrates the effectiveness and superiority of the proposed method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Neurocomputing
Neurocomputing 工程技术-计算机:人工智能
CiteScore
13.10
自引率
10.00%
发文量
1382
审稿时长
70 days
期刊介绍: Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信