Automatic model reduction of differential algebraic systems by proper orthogonal decomposition

被引：2

作者：

Khlopov, Dmytro ^{[1
]}

Mangold, Michael ^{[2
]}

机构：

[1] Max Planck Inst Dynam Complex Tech Syst, Sandtorstr 1, D-39106 Magdeburg, Germany

[2] Tech Hsch Bingen, Berlinstr 109, D-55411 Bingen, Germany

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2017年 / 97卷

关键词：

Nonlinear model reduction; Proper orthogonal decomposition; Empirical interpolation; Computer aided modeling; Differential algebraic systems; POINTS INTERPOLATION; EQUATIONS; DYNAMICS; MOMENTS;

D O I：

10.1016/j.compchemeng.2016.11.004

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Proper orthogonal decomposition (POD) is an attractive way to obtain nonlinear low-dimensional models. This article reports on the automatization of the mentioned reduction method. An automatic procedure for the reduction of differential algebraic systems is presented, which is implemented in the modeling and simulation environment ProMoT/Diana. The software tool has been applied to a nonlinear heat conduction model and a continuous fluidized bed crystallizer model. The automatically generated reduced models are significantly smaller than the reference models, while the loss of accuracy is negligible. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：104 / 113

页数：10

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