带脉冲的离散时随机系统的几乎确定的指数稳定性和随机稳定性

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED Journal of Computational and Applied Mathematics Pub Date : 2024-07-22 DOI:10.1016/j.cam.2024.116152
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引用次数: 0

摘要

本文研究了具有脉冲效应的离散时间随机系统(DTSSs)的几乎确定指数稳定性和随机稳定问题,其中考虑了平均脉冲间隔。利用平均脉冲间隔法和强大数定律,我们不仅建立了一般非线性离散时间脉冲随机系统(DTISSs)的几乎确定指数稳定性准则,而且设计了一种随机扰动的精确方法来稳定给定的不稳定脉冲离散时间系统。采用平均冲动区间法和强大数定律,我们建立了一般非线性 DTISSs 几乎确定的指数稳定性准则。此外,我们还开发了一种随机扰动方法来稳定不稳定的脉冲离散时间系统。最后,两个仿真实例证明了推导结果的有效性。
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Almost sure exponential stability and stochastic stabilization of discrete-time stochastic systems with impulses

This paper considers the almost sure exponential stability and stochastic stabilization problems of discrete-time stochastic systems (DTSSs) with impulsive effects, where the average impulsive interval is taken into account. By using the average impulsive interval approach and the strong law of large numbers, we not only establish the criteria for almost sure exponential stability of general nonlinear discrete-time impulsive stochastic systems (DTISSs) but also design an exact method of a stochastic perturbation to stabilize a given unstable impulsive discrete-time systems. Adopting the average impulsive interval approach and the strong law of large numbers, we established a criterion for almost sure exponential stability of general nonlinear DTISSs. Furthermore, a method of stochastic perturbation has been developed to stabilize an unstable impulsive discrete-time system. Finally, two simulation examples demonstrate the effectiveness of the derived results.

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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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