R-L分数阶时滞系统的稳定性及其在时滞脉冲网络同步中的应用

IF 6.3 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xiaofei Xing , Lifei Wang , Huaiqin Wu , Jinde Cao , Xiao Peng
{"title":"R-L分数阶时滞系统的稳定性及其在时滞脉冲网络同步中的应用","authors":"Xiaofei Xing ,&nbsp;Lifei Wang ,&nbsp;Huaiqin Wu ,&nbsp;Jinde Cao ,&nbsp;Xiao Peng","doi":"10.1016/j.neunet.2025.107690","DOIUrl":null,"url":null,"abstract":"<div><div>This paper focuses on the <span><math><mi>θ</mi></math></span>-exponential synchronization for fractional-order complex networks (FOCNs) with Riemann–Liouville (R-L) fractional order, hybrid couplings, and short memory under delayed impulse effects. Firstly, A new <span><math><mi>θ</mi></math></span>-exponential stability criterion, which plays a crucial role for the network synchronization analysis later, is developed for delayed systems with R-L fractional order under delayed impulse effects, where the impulses can be stable or unstable, see Theorem 2.1. Secondly, the system model with respect to impulsive FOCNs with hybrid couplings and short memory under delayed impulse effects is established in the sense of R-L, which is more universal and practical. The novel feedback controller and adaptive feedback controller, are designed to realize the <span><math><mi>θ</mi></math></span>-exponential synchronization objective, respectively. In addition, by utilizing Lyapunov functional approach, fractional calculus, matrix inequality analysis techniques and proposed stability criterion, the <span><math><mi>θ</mi></math></span>-exponential synchronization conditions, which are associated with time delay and the order of systems, are derived in the form of linear matrix inequalities (LMIs). Finally, the numerical simulation result for Chua’s circuit networks, is provided to illustrate the validity of the obtained result and the effectiveness of the proposed control approach.</div></div>","PeriodicalId":49763,"journal":{"name":"Neural Networks","volume":"190 ","pages":"Article 107690"},"PeriodicalIF":6.3000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stability of delayed systems with R-L fractional order and application to synchronization in networks with delayed impulses\",\"authors\":\"Xiaofei Xing ,&nbsp;Lifei Wang ,&nbsp;Huaiqin Wu ,&nbsp;Jinde Cao ,&nbsp;Xiao Peng\",\"doi\":\"10.1016/j.neunet.2025.107690\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper focuses on the <span><math><mi>θ</mi></math></span>-exponential synchronization for fractional-order complex networks (FOCNs) with Riemann–Liouville (R-L) fractional order, hybrid couplings, and short memory under delayed impulse effects. Firstly, A new <span><math><mi>θ</mi></math></span>-exponential stability criterion, which plays a crucial role for the network synchronization analysis later, is developed for delayed systems with R-L fractional order under delayed impulse effects, where the impulses can be stable or unstable, see Theorem 2.1. Secondly, the system model with respect to impulsive FOCNs with hybrid couplings and short memory under delayed impulse effects is established in the sense of R-L, which is more universal and practical. The novel feedback controller and adaptive feedback controller, are designed to realize the <span><math><mi>θ</mi></math></span>-exponential synchronization objective, respectively. In addition, by utilizing Lyapunov functional approach, fractional calculus, matrix inequality analysis techniques and proposed stability criterion, the <span><math><mi>θ</mi></math></span>-exponential synchronization conditions, which are associated with time delay and the order of systems, are derived in the form of linear matrix inequalities (LMIs). Finally, the numerical simulation result for Chua’s circuit networks, is provided to illustrate the validity of the obtained result and the effectiveness of the proposed control approach.</div></div>\",\"PeriodicalId\":49763,\"journal\":{\"name\":\"Neural Networks\",\"volume\":\"190 \",\"pages\":\"Article 107690\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Networks\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0893608025005702\",\"RegionNum\":1,\"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":"Neural Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0893608025005702","RegionNum":1,"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

本文研究了具有Riemann-Liouville (R-L)分数阶、混合耦合和短记忆的分数阶复杂网络(focn)在延迟脉冲效应下的θ-指数同步。首先,对于延迟脉冲效应下的R-L分数阶延迟系统,提出了一个新的θ-指数稳定性判据,该判据对后续的网络同步分析起着至关重要的作用,其中脉冲可以是稳定的,也可以是不稳定的,见定理2.1。其次,从R-L的意义上建立了延迟脉冲效应下具有混合耦合和短记忆的脉冲focn的系统模型,该模型更具通用性和实用性。设计了新型反馈控制器和自适应反馈控制器,分别实现了θ-指数同步目标。此外,利用Lyapunov泛函方法、分数阶微积分、矩阵不等式分析技术和提出的稳定性判据,以线性矩阵不等式(lmi)的形式导出了与时滞和系统阶数相关的θ-指数同步条件。最后,给出了蔡氏电路网络的数值仿真结果,验证了所得结果的有效性和所提控制方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stability of delayed systems with R-L fractional order and application to synchronization in networks with delayed impulses
This paper focuses on the θ-exponential synchronization for fractional-order complex networks (FOCNs) with Riemann–Liouville (R-L) fractional order, hybrid couplings, and short memory under delayed impulse effects. Firstly, A new θ-exponential stability criterion, which plays a crucial role for the network synchronization analysis later, is developed for delayed systems with R-L fractional order under delayed impulse effects, where the impulses can be stable or unstable, see Theorem 2.1. Secondly, the system model with respect to impulsive FOCNs with hybrid couplings and short memory under delayed impulse effects is established in the sense of R-L, which is more universal and practical. The novel feedback controller and adaptive feedback controller, are designed to realize the θ-exponential synchronization objective, respectively. In addition, by utilizing Lyapunov functional approach, fractional calculus, matrix inequality analysis techniques and proposed stability criterion, the θ-exponential synchronization conditions, which are associated with time delay and the order of systems, are derived in the form of linear matrix inequalities (LMIs). Finally, the numerical simulation result for Chua’s circuit networks, is provided to illustrate the validity of the obtained result and the effectiveness of the proposed control approach.
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
Neural Networks
Neural Networks 工程技术-计算机:人工智能
CiteScore
13.90
自引率
7.70%
发文量
425
审稿时长
67 days
期刊介绍: Neural Networks is a platform that aims to foster an international community of scholars and practitioners interested in neural networks, deep learning, and other approaches to artificial intelligence and machine learning. Our journal invites submissions covering various aspects of neural networks research, from computational neuroscience and cognitive modeling to mathematical analyses and engineering applications. By providing a forum for interdisciplinary discussions between biology and technology, we aim to encourage the development of biologically-inspired artificial intelligence.
×
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