POD-galerkin approximations in PDE-constrained optimization

被引：0
|
作者：
Sachs E.W. [1 ]
Volkwein S. [2 ]
机构：
[1] FB 4 - Department of Mathematics, University of Trier
[2] Department of Mathematics and Statistics, University of Constance
来源：
GAMM Mitteilungen | 2010年 / 33卷 / 02期
关键词：
Proper orthogonal decomposition; Reduced-order modelling;
D O I：
10.1002/gamm.201010015
中图分类号：
学科分类号：
摘要：
Proper orthogonal decomposition (POD) is one of the most popular model reduction techniques for nonlinear partial differential equations. It is based on a Galerkin-type approximation, where the POD basis functions contain information from a solution of the dynamical system at pre-specified time instances, so-called snapshots. POD models have been applied very successfully in the area of optimization with PDEs or feedback control laws. Neverthe-less, various issues are still unclear and are currently under research, e.g. timely updates of the snapshot information and error analyses for the POD approximations. © WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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收藏
页码：194 / 208
页数：14
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