{"title":"具有时滞的分数阶脉冲系统的有限时间收缩稳定性","authors":"P. Gokul, Salem Ben Said","doi":"10.1016/j.cnsns.2025.109050","DOIUrl":null,"url":null,"abstract":"<div><div>This article presents a new perspective on finite-time stability (FTS) and finite-time contractive stability (FTCS) for fractional-order impulsive system (FOIS) with dual delays that depend on both state and time. By integrating impulsive control theory with the Lyapunov function (LF) method, we establish comprehensive stability criteria for stabilizing and destabilizing impulses. We further apply these results to two types of fractional-order neural networks (FONNs): fractional-order delayed neural networks (FODNNs) and fractional-order Cohen–Grossberg neural networks (FOCGNNs), both incorporating dual delays and impulse phenomena. Numerical simulations rigorously validate our theoretical findings, demonstrating the effectiveness and practical relevance of the proposed approach.</div></div>","PeriodicalId":50658,"journal":{"name":"Communications in Nonlinear Science and Numerical Simulation","volume":"151 ","pages":"Article 109050"},"PeriodicalIF":3.8000,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Finite-time contractive stability for fractional-order impulsive systems with time delays\",\"authors\":\"P. Gokul, Salem Ben Said\",\"doi\":\"10.1016/j.cnsns.2025.109050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This article presents a new perspective on finite-time stability (FTS) and finite-time contractive stability (FTCS) for fractional-order impulsive system (FOIS) with dual delays that depend on both state and time. By integrating impulsive control theory with the Lyapunov function (LF) method, we establish comprehensive stability criteria for stabilizing and destabilizing impulses. We further apply these results to two types of fractional-order neural networks (FONNs): fractional-order delayed neural networks (FODNNs) and fractional-order Cohen–Grossberg neural networks (FOCGNNs), both incorporating dual delays and impulse phenomena. Numerical simulations rigorously validate our theoretical findings, demonstrating the effectiveness and practical relevance of the proposed approach.</div></div>\",\"PeriodicalId\":50658,\"journal\":{\"name\":\"Communications in Nonlinear Science and Numerical Simulation\",\"volume\":\"151 \",\"pages\":\"Article 109050\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications in Nonlinear Science and Numerical Simulation\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1007570425004617\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Nonlinear Science and Numerical Simulation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1007570425004617","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Finite-time contractive stability for fractional-order impulsive systems with time delays
This article presents a new perspective on finite-time stability (FTS) and finite-time contractive stability (FTCS) for fractional-order impulsive system (FOIS) with dual delays that depend on both state and time. By integrating impulsive control theory with the Lyapunov function (LF) method, we establish comprehensive stability criteria for stabilizing and destabilizing impulses. We further apply these results to two types of fractional-order neural networks (FONNs): fractional-order delayed neural networks (FODNNs) and fractional-order Cohen–Grossberg neural networks (FOCGNNs), both incorporating dual delays and impulse phenomena. Numerical simulations rigorously validate our theoretical findings, demonstrating the effectiveness and practical relevance of the proposed approach.
期刊介绍:
The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity.
The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged.
Topics of interest:
Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity.
No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Rapid Communications. Discussions of previously published papers are welcome.