Delay-compensatory-based event-triggering impulsive control on uncertain chaotic neural networks via average delayed impulsive gains

IF 3.8 2区数学 Q1 MATHEMATICS, APPLIED

Communications in Nonlinear Science and Numerical Simulation Pub Date : 2025-09-23 DOI:10.1016/j.cnsns.2025.109311

Ziqing Geng , Dong Ding , Ze Tang , Jianwen Feng

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引用次数: 0

Abstract

This article investigates the exponential synchronization problem of chaotic neural networks (NNs) subject to time-varying delays and parametric uncertainty in conjunction with the event-triggering hybrid impulsive control method and delay compensatory strategy. In view of the limited available communication resources, the event-triggering delayed impulsive control (ETDIC) strategy which effectively incorporates the merits of both event-triggering protocol and delayed impulsive control is formulated. Meanwhile, the concept of average delayed impulsive gains (ADIG) and extended comparison principle are developed to solve the challenges posed by the time-varying gains and flexible delays in the impulsive controller, which not only diminish the constraints on time delay but also suggest that the delay could compensate for the desynchronizing delayed impulses dynamics. Together with the parameter variation formula method and the delay compensatory scheme, sufficient relaxed conditions for exponential synchronization are derived. Furthermore, the convergence rate is precisely estimated and the Zeno behavior is eliminated. Finally, a numerical example is presented along with some comparisons to validate the theoretical analysis.

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基于延迟补偿的不确定混沌神经网络平均延迟脉冲增益事件触发脉冲控制

结合事件触发混合脉冲控制方法和延迟补偿策略，研究时变时滞和参数不确定性下混沌神经网络的指数同步问题。针对有限的可用通信资源，提出了一种有效结合事件触发协议和延迟脉冲控制优点的事件触发延迟脉冲控制策略。同时，提出了平均延迟脉冲增益（ADIG）的概念和扩展比较原理，解决了脉冲控制器中时变增益和柔性延迟所带来的挑战，不仅减少了对时延的约束，而且表明时延可以补偿失同步的延迟脉冲动力学。结合参数变分公式法和延迟补偿方案，导出了指数同步的充分松弛条件。此外，精确估计了收敛速度，消除了芝诺行为。最后给出了数值算例并进行了比较，验证了理论分析的正确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Communications in Nonlinear Science and Numerical Simulation MATHEMATICS, APPLIED-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

CiteScore

6.80

自引率

7.70%

发文量

378

审稿时长

78 days

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.