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Sampled-data stabilization for a kind of stochastic nonlinear systems driven by G-Brownian motion

机译:G-Brownian运动驱动的一种随机非线性系统的采样数据稳定

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In this paper, we analyzed the mean-square exponential stability of controlled stochastic differential equations driven by G-Brownian motion(G-SDEs) based on their approximate discrete-time models. Firstly, Euler-Maruyama(EM) approximation model is established for such systems. Meanwhile, we investigated the one-step consistency between exact discrete-time model and EM approximation model of the original system. Then, the stability relationship between the EM approximation model and its exact model is studied. Finally, a numerical simulation is presented to verify the effect of our results.
机译:在本文中,我们基于其近似离散时间模型分析了G-Brownian运动(G-SDE)驱动的受控随机微分方程的平均方指数稳定性。首先,为这些系统建立了欧拉 - 玛雅(EM)近似模型。同时,我们调查了原始系统的精确离散时间模型与EM近似模型之间的一步一致性。然后,研究了EM近似模型与其精确模型之间的稳定性关系。最后,提出了数值模拟以验证结果的效果。

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