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An incomplete modal method for eigenvector derivatives of polynomial eigenvalue problems

机译:多项式特征值问题的特征衍生物的不完全模态方法

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Eigenvector derivatives of eigenproblems analytically dependent on parameters are required in diverse technical fields such as structural design, system identification. Modal methods, a kind of popular methods in engineering problems, calculate eigenvector derivatives by expressing them as linear combinations of eigenvectors of eigenproblems. In this paper, an incomplete modal method is presented to compute eigenvector derivatives of polynomial eigenproblems analytically dependent on parameters. The proposed method only uses a small part of eigenvectors of polynomial eigenproblems. The contributions of other eigenvectors to eigenvector derivatives are approximated by an iterative formula. Our method can simultaneously compute the eigenvector derivatives corresponding to several eigenvalues, and it is effective whether the differentiated eigenvectors correspond to simple or semisimple eigenvalues, and whether the leading coefficient matrix is singular or not. Numerical examples are given to test the efficiency of the proposed method.
机译:在各种技术领域等各种技术领域需要分析参数的特征向量衍生物,如结构设计,系统识别。模态方法,一种工程问题中的流行方法,通过表达它们作为特征预测的线性组合来计算特征病衍生物。本文提出了一种不完整的模态方法,以计算分析依赖于参数的多项式特征问题的特征vector衍生物。所提出的方法仅使用多项式特征向量的小部分。其他特征向量对特征传感器衍生物的贡献近似于迭代公式。我们的方法可以同时计算对应于若干特征值的特征向量衍生物,并且差分的特征向量是对应于简单的或半精心值的有效性,以及前导系数矩阵是否是奇异的。给出了数值例子来测试所提出的方法的效率。

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