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Nonlinear model order reduction based on tensor Kronecker product expansion with Arnoldi process

机译:基于张量Kronecker乘积和Arnoldi展开的非线性模型降阶

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摘要

In this paper, we present a model order reduction (MOR) method for large nonlinear input output systems based on tensor Kronecker product expansion with Arnoldi process. We first approximate the nonlinear system with a quadratic form at single-point expansion, and then use a tensor Kronecker product analysis to it. Constructing the projection matrix through solving a linear equation, a reduced quadratic system is produced, which can match the first several expansion coefficients of the original output. What is more, it can preserve the stability and passivity under some certain conditions as well. The error estimation is also well discussed. Finally, the robust behavior of our MOR method is successfully illustrated via two numerical examples. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:在本文中,我们提出了基于张量Kronecker乘积与Arnoldi过程的大型非线性输入输出系统的模型降阶(MOR)方法。我们首先在单点展开时以二次形式近似非线性系统,然后对其进行张量Kronecker乘积分析。通过求解线性方程来构造投影矩阵,生成了一个简化的二次系统,该二次系统可以匹配原始输出的前几个扩展系数。而且,它还可以在某些条件下保持稳定性和无源性。误差估计也得到了很好的讨论。最后,通过两个数值示例成功地说明了我们的MOR方法的鲁棒性。 (C)2016富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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  • 来源
    《Journal of the Franklin Institute》 |2016年第14期|3641-3655|共15页
  • 作者单位

    Xi An Jiao Tong Univ, Sch Math & Stat, Xian 710049, Shaanxi, Peoples R China;

    Xi An Jiao Tong Univ, Sch Math & Stat, Xian 710049, Shaanxi, Peoples R China;

    Xi An Jiao Tong Univ, Sch Math & Stat, Xian 710049, Shaanxi, Peoples R China;

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  • 入库时间 2022-08-18 02:57:49

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