Krylov Subspace Methods for Model Order Reduction in Computational Electromagnetics

被引：5

作者：

Bonotto, Matteo ^{[1
]}

Cenedese, Angelo ^{[2
]}

Bettini, Paolo ^{[3
]}

机构：

[1] Univ Padua, CRF, Padua, Italy

[2] Univ Padua, Dept Informat Engn, Padua, Italy

[3] Univ Padua, Dept Ind Engn, Padua, Italy

来源：

IFAC PAPERSONLINE | 2017年 / 50卷 / 01期

关键词：

Model order reduction (MOR); Krylov subspace method; Arnoldi algorithm; Computational Electromagnetics; DYNAMICAL-SYSTEMS;

D O I：

10.1016/j.ifacol.2017.08.1019

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a model order reduction method via Krylov subspace projection, for applications in the field of computational electromagnetics (CEM). The approach results to be suitable both for SISO and MIMO systems, and is based on the numerically robust Arnoldi procedure. We have studied the model order reduction as the number of inputs and outputs changes, to better understand the behavior of the reduction technique. Relevant CEM examples related to the reduction of finite element method models are presented to validate this methodology, both in the 2D and in the 3D case. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：6355 / 6360

页数：6

共 16 条

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