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Probabilistic response of dynamical systems based on the global attractor with the compatible cell mapping method

机译:基于全局吸引子与兼容小区映射方法的动态系统的概率响应

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摘要

A generalized compatible cell mapping (CCM) method is proposed in this paper to take advantages of the simple cell mapping (SCM) method, the generalized cell mapping (GCM) method together with a subdivision procedure. A coarse cell partition is first used to obtain a covering set of the global attractor. Then, a finer global attractor is obtained by the subdivision process. The probabilistic response of stochastic dynamic systems is obtained by the sparse matrix analysis algorithm applied to the covering set of the global attractor. Because the computational domain is the covering set of the global attractor rather than the whole state space, the numerical efficiency of the proposed method can be greatly improved as compared to the GCM. A three-dimensional and a four-dimensional dynamical system under Poisson white noise excitation are studied to demonstrate the effectiveness of the proposed method for the probabilistic response analysis. Monte Carlo simulations show a good agreement with the proposed method. (C) 2018 Elsevier B.V. All rights reserved.
机译:在本文中提出了一种广义兼容小区映射(CCM)方法,以利用简单的小区映射(SCM)方法,广义细胞映射(GCM)方法以及细分过程。首先用于获得全局吸引子的覆盖集的粗细胞分区。然后,通过细分过程获得更精细的全局吸引子。随机动态系统的概率响应是通过应用于全局吸引子的覆盖集的稀疏矩阵分析算法获得。因为计算域是全局吸引子的覆盖集而不是整个状态空间,所以与GCM相比,所提出的方法的数值效率可以大大提高。研究了泊松白噪声激发下的三维和四维动力学系统,以证明所提出的概率反应分析方法的有效性。 Monte Carlo模拟与所提出的方法吻合良好。 (c)2018年elestvier b.v.保留所有权利。

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