Computationally Efficient Simulations of Stochastically Perturbed Nonlinear Dynamical Systems
Computationally Efficient Simulations of Stochastically Perturbed Nonlinear Dynamical Systems
复制标题
随机扰动非线性动力系统的计算高效模拟
DOI：
10.1115/1.4054932
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发表时间：
2022
影响因子：
2
通讯作者：
Balachandran, Balakumar
中科院分区：
文献类型：
--
作者：
Breunung, Thomas;Balachandran, Balakumar
需要一种概率方法来处理在自然过程和工程应用中产生的不确定性系统。然而，为了计算方便，通常忽略随机效应。因此，随机动力系统的数值积分程序与确定性情况的数值积分程序相比是基本的。在这项工作中，作者提出了一种方法，通过使用为确定性情况开发的方法来进行随机模拟。因此，为确定性系统开发的完善的数值积分程序可用于随机系统的研究。通过算例说明了该方法的收敛性，并证明了该方法的性能。
A probabilistic approach is needed to address systems with uncertainties arising in natural processes and engineering applications. For computational convenience, however, the stochastic effects are often ignored. Thus, numerical integration routines for stochastic dynamical systems are rudimentary compared to those for the deterministic case. In this work, the authors present a method to carry out stochastic simulations by using methods developed for the deterministic case. Thereby, the well-developed numerical integration routines developed for deterministic systems become available for studies of stochastic systems. The convergence of the developed method is shown and the method's performance is demonstrated through illustrative examples.