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.
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页码：3 / +
页数：2
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