Sampled-data stabilization for a class of stochastic nonlinear systems with Markovian switching based on the approximate discrete-time models*

Peilong Yu, Yu Kang, Qianqian Zhang
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引用次数: 5

Abstract

The mean-square exponential stability of a class of stochastic differential equations with Markovian switching(SDEwMS) by sampled-data control is investigated. We introduce a new controller design idea for such kind of systems based on its approximate discrete-time model(ADTM). Comparing with the existing results, this controller design method(CDM) is simpler and easier to calculate. Meanwhile, We study the multi-step model error between the SDEwMS and its Euler-Maruyama(EM) model. The effectiveness of our results is demonstrated by a numerical simulation.
一类基于近似离散时间模型的马尔可夫切换随机非线性系统的采样数据镇定
研究了一类具有马尔可夫切换的随机微分方程在抽样数据控制下的均方指数稳定性。提出了一种基于近似离散时间模型(ADTM)的控制器设计思想。与已有的结果相比,该控制器设计方法(CDM)更简单,更易于计算。同时,我们研究了SDEwMS与其Euler-Maruyama(EM)模型之间的多步模型误差。通过数值模拟验证了所得结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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