Accuracy enhancing methods for the frequency-weighted balancing related model reduction

Andras Varga; Brian D.O. Anderson

doi:10.1109/CDC.2001.980430

Accuracy enhancing methods for the frequency-weighted balancing related model reduction

Andras Varga
, Brian D.O. Anderson

Research output: Contribution to journal › Article › peer-review

25 Citations (Scopus)

Abstract

In this paper we develop computational techniques with enhanced accuracy for two frequency-weighted model reduction approaches, namely, balanced truncation, and singular perturbation approximation. New stability-enforcing choices of the frequency-weighted grammians can guarantee the stability of reduced models for two-sided frequency weights. Several numerical examples show the effectiveness of the new approximation techniques.

Original language	English
Pages (from-to)	3659-3664
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	4
DOIs	https://doi.org/10.1109/CDC.2001.980430
Publication status	Published - 2001

Access to Document

10.1109/CDC.2001.980430

Cite this

@article{38bcfd24bc5049dd9fd58cc543833eee,

title = "Accuracy enhancing methods for the frequency-weighted balancing related model reduction",

abstract = "In this paper we develop computational techniques with enhanced accuracy for two frequency-weighted model reduction approaches, namely, balanced truncation, and singular perturbation approximation. New stability-enforcing choices of the frequency-weighted grammians can guarantee the stability of reduced models for two-sided frequency weights. Several numerical examples show the effectiveness of the new approximation techniques.",

author = "Andras Varga and Anderson, \{Brian D.O.\}",

year = "2001",

doi = "10.1109/CDC.2001.980430",

language = "English",

volume = "4",

pages = "3659--3664",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0743-1546",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Accuracy enhancing methods for the frequency-weighted balancing related model reduction

AU - Varga, Andras

AU - Anderson, Brian D.O.

PY - 2001

Y1 - 2001

N2 - In this paper we develop computational techniques with enhanced accuracy for two frequency-weighted model reduction approaches, namely, balanced truncation, and singular perturbation approximation. New stability-enforcing choices of the frequency-weighted grammians can guarantee the stability of reduced models for two-sided frequency weights. Several numerical examples show the effectiveness of the new approximation techniques.

AB - In this paper we develop computational techniques with enhanced accuracy for two frequency-weighted model reduction approaches, namely, balanced truncation, and singular perturbation approximation. New stability-enforcing choices of the frequency-weighted grammians can guarantee the stability of reduced models for two-sided frequency weights. Several numerical examples show the effectiveness of the new approximation techniques.

UR - https://www.scopus.com/pages/publications/0035713871

U2 - 10.1109/CDC.2001.980430

DO - 10.1109/CDC.2001.980430

M3 - Article

SN - 0743-1546

VL - 4

SP - 3659

EP - 3664

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

ER -

Accuracy enhancing methods for the frequency-weighted balancing related model reduction

Abstract

Access to Document

Other files and links

Fingerprint

Cite this