DocumentCode
2138576
Title
An iterative SVD-Krylov based algorithm for model reduction of MIMO systems
Author
Yu´e An ; Dong Zhang
Author_Institution
Dept. of Appl. Math., Shanghai Finance Univ., Shanghai, China
fYear
2013
fDate
23-25 July 2013
Firstpage
1016
Lastpage
1020
Abstract
In this paper we propose a model reduction algorithm for approximation of large-scale MIMO systems, which combines the SVD and Krylov based techniques. The reduced model is also asymptotically stable and a tangential condition can be satisfied. Numerical examples demonstrate the performance of the proposed approach and we compare it with the existing method MIRIA.
Keywords
MIMO systems; approximation theory; asymptotic stability; iterative methods; regression analysis; support vector machines; MIMO systems; MIRIA; asymptotically stability; iterative SVD Krylov based algorithm; model reduction algorithm; tangential condition; Asymptotic stability; Interpolation; MIMO; Numerical stability; Reduced order systems; Stability analysis; Transfer functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location
Shenyang
Type
conf
DOI
10.1109/ICNC.2013.6818125
Filename
6818125
Link To Document