Optimal reduced-order modeling for nonlinear distributed parameter systems

被引：5
|
作者：
Borggaard, Jeff [1 ]
机构：
[1] Virginia Tech, Dept Math, Blacksburg, VA 24061 USA
来源：
2006 AMERICAN CONTROL CONFERENCE, VOLS 1-12 | 2006年 / 1-12卷
关键词：
D O I：
10.1109/ACC.2006.1656372
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A method to develop reduced-order models for nonlinear distributed parameter systems is studied. The method is based on Galerkin projection, but the reduced-basis vectors are optimal for the dynamic model, found by minimizing the error between given full-order simulation data and the reduced-order model. This is achieved by formulating the basis selection problem as an optimal control problem with the reduced-order model as a constraint. This methodology allows a natural extension of reduced-order modeling ideas to nonlinear systems. A numerical experiment comparing the optimal reduced-order model to the popular proper orthogonal decomposition method is provided.
引用
收藏
页码：1150 / 1154
页数：5
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