Data-driven model reduction for weakly nonlinear systems: A summary

被引：0

作者：

Antoulas, A. C. ^{[1
,2
]}

Gosea, I. V. ^{[2
]}

机构：

[1] Rice Univ, Dept Elect & Comp Engn, POB 1892, Houston, TX 77251 USA

[2] Jacobs Univ Bremen, Sch Sci & Engn, D-28759 Bremen, Germany

来源：

IFAC PAPERSONLINE | 2015年 / 48卷 / 01期

关键词：

D O I：

10.1016/j.ifacol.2015.05.123

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Model reduction seeks to replace complex dynamical systems with simpler ones, having similar characteristics. One approach is data-driven reduction based on system data which are either measured or computed. In this regard the Loewner framework is a powerful tool for dealing with the reduction of both linear and nonlinear systems. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：3 / +

页数：2

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