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

机译:基于近似离散时间模型的带马尔可夫切换的一类随机非线性系统的采样数据稳定化 *

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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.
机译:研究了通过采样数据控制与马尔科维亚交换机(SDEWMS)的一类随机微分方程的平均方形指数稳定性。基于其近似离散时间模型(ADTM),我们为这种系统提供了新的控制器设计思路。与现有结果相比,该控制器设计方法(CDM)更简单,更易于计算。同时,我们研究SDEWMS及其欧拉 - 玛雅(EM)模型之间的多步模型错误。通过数值模拟证明了我们的结果的有效性。

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