Hilbert-Schmidt-Hankel norm model reduction for matrix second-order linear systems

Qing Wang; Tongke Zhong; Ngai Wong; Qingyang Wang

doi:10.1007/s11768-011-9300-6

Hilbert-Schmidt-Hankel norm model reduction for matrix second-order linear systems

Qing Wang, Tongke Zhong, Ngai Wong, Qingyang Wang

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

1 Citation (Scopus)

Abstract

This paper considers the optimal model reduction problem of matrix second-order linear systems in the sense of Hilbert-Schmidt-Hankel norm, with the reduced order systems preserving the structure of the original systems. The expressions of the error function and its gradient are derived. Two numerical examples are given to illustrate the presented model reduction technique.

Original language	English
Pages (from-to)	571-578
Number of pages	8
Journal	Journal of Control Theory and Applications
Volume	9
Issue number	4
DOIs	https://doi.org/10.1007/s11768-011-9300-6
Publication status	Published - Nov 2011
Externally published	Yes

Keywords

Gradient
Hilbert-Schmidt-Hankel norm
Matrix second-order linear system
Model reduction

ASJC Scopus subject areas

Control and Systems Engineering
Hardware and Architecture
Computer Science Applications

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s11768-011-9300-6

Cite this

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title = "Hilbert-Schmidt-Hankel norm model reduction for matrix second-order linear systems",

abstract = "This paper considers the optimal model reduction problem of matrix second-order linear systems in the sense of Hilbert-Schmidt-Hankel norm, with the reduced order systems preserving the structure of the original systems. The expressions of the error function and its gradient are derived. Two numerical examples are given to illustrate the presented model reduction technique.",

keywords = "Gradient, Hilbert-Schmidt-Hankel norm, Matrix second-order linear system, Model reduction",

author = "Qing Wang and Tongke Zhong and Ngai Wong and Qingyang Wang",

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AU - Wang, Qing

AU - Zhong, Tongke

AU - Wong, Ngai

AU - Wang, Qingyang

PY - 2011/11

Y1 - 2011/11

N2 - This paper considers the optimal model reduction problem of matrix second-order linear systems in the sense of Hilbert-Schmidt-Hankel norm, with the reduced order systems preserving the structure of the original systems. The expressions of the error function and its gradient are derived. Two numerical examples are given to illustrate the presented model reduction technique.

AB - This paper considers the optimal model reduction problem of matrix second-order linear systems in the sense of Hilbert-Schmidt-Hankel norm, with the reduced order systems preserving the structure of the original systems. The expressions of the error function and its gradient are derived. Two numerical examples are given to illustrate the presented model reduction technique.

KW - Gradient

KW - Hilbert-Schmidt-Hankel norm

KW - Matrix second-order linear system

KW - Model reduction

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M3 - Article

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JO - Journal of Control Theory and Applications

JF - Journal of Control Theory and Applications

IS - 4

ER -

Hilbert-Schmidt-Hankel norm model reduction for matrix second-order linear systems

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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