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Stochastic stability of quasi-integrable and non-resonant Hamiltonian systems under parametric excitations of combined Gaussian and Poisson white noises

机译:高斯和泊松混合白噪声参数激励下拟可积分和非共振哈密顿系统的随机稳定性

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摘要

A procedure for calculating the largest Lyapunov exponent and determining the asymptotic Lyapunov stability with probability one of multi-degree-of-freedom (MDOF) quasi-integrable and non-resonant Hamiltonian systems under parametric excitations of combined Gaussian and Poisson white noises is proposed. The averaged stochastic differential equations (SDEs) of quasi-integrable and non-resonant Hamiltonian systems subject to parametric excitations of combined Gaussian and Poisson white noises are first derived by using the stochastic averaging method for quasi-Hamiltonian systems and the stochastic jump-diffusion chain rule. Then, the expression for the largest Lyapunov exponent is obtained by generalizing Khasminskii's procedure to the averaged SDEs and the stochastic stability of the original systems is determined approximately. An example is given to illustrate the application of the proposed procedure and its effectiveness is verified by comparing with the results from Monte Carlo simulation.
机译:提出了一种计算高Lyapunov指数并确定渐近Lyapunov稳定性的程序,该概率具有多自由度(MDOF)拟可积和非共振哈密顿系统,在组合高斯和泊松白噪声的参数激励下具有概率。首先使用准哈密顿系统的随机平均方法和随机跳-扩散链,推导受高斯和泊松混合白噪声参数激励的准可积分和非共振哈密顿系统的平均随机微分方程(SDE)。规则。然后,通过将Khasminskii程序推广到平均SDE来获得最大Lyapunov指数的表达式,并大致确定原始系统的随机稳定性。举例说明了所提方法的应用,并与蒙特卡罗模拟的结果进行了比较,验证了其有效性。

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