Principal components analysis in sensitivity studies of dynamic systems

被引：17

作者：

Perry, M. A. ^{[1
]}

Wynn, H. P. ^{[1
]}

Bates, R. A. ^{[1
]}

机构：

[1] Univ London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, England

来源：

PROBABILISTIC ENGINEERING MECHANICS | 2006年 / 21卷 / 04期

关键词：

dynamic modeling; sensitivity analysis; principal component analysis; system robustness;

D O I：

10.1016/j.probengmech.2006.05.005

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Local sensitivity analysis is a modeling tool for determining the effects of single parameter variations on the output of a first order differential system. To determine the effects of multi-parameter variations, the local sensitivity matrix can be used in a first order Taylor series to approximately model the variance of the system output. For dynamic systems, a principal component analysis based on this time varying approximation reveals the evolution of the directions and magnitudes of greatest variation of the system output derived from input variability in the parameters. Such an analysis acts as a means of modeling the robustness of dynamic differential systems. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：454 / 460

页数：7

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