Model Order Reduction for Parameter Dependent Substructured Systems using Krylov Subspaces

被引:3
作者
Walker, Nadine [1 ]
Froehlich, Benjamin [1 ]
Eberhard, Peter [1 ]
机构
[1] Univ Stuttgart, Inst Engn & Computat Mech, Stuttgart, Germany
来源
IFAC PAPERSONLINE | 2018年 / 51卷 / 02期
关键词
model order reduction; modular setup; parametric systems; moment matching; second order systems;
D O I
10.1016/j.ifacol.2018.03.093
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
During the development of technical products, different components are usually designed and modelled in different departments leading to a modular setup of technical systems and simulation models. Therefore, it is desirable to perform model order reduction on component level and to assemble the reduced systems. In this context, moment matching methods have shown to be advantageous, since moments matched on component level are still matched in the assembled system. In this contribution these moment matching properties of systems within a modular setup are extended to parametric systems with a modular setup. It will be shown that parametric moment matching on component level delivers an assembled parametric system in which the transfer function and its gradient are matched at desired parameter samples. The theoretical results are illustrated with a numerical example. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:553 / 558
页数:6
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