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 , N. Padmaja , E. Umamaheswari , 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 , N. Padmaja , E. Umamaheswari , 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}
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 and . 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.
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.