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		Qing WANG,Tongke ZHONG,Ngai WONG,Qingyang WANG.[en_title][J].Control Theory and Technology,2011,9(4):571~578.[Copy]

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QingWANG,TongkeZHONG,NgaiWONG,QingyangWANG
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(School of information Science and Technology, Sun Yat-Sen University; Department of Electrical and Electronic Engineering, The University of Hong Kong;School of Electric Power, South China University of Technology;College of Automation and Engineering, South China University of Technology)

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Received:December 18, 2009Revised:July 04, 2010

基金项目:This work was supported by the National Nature Science Foundation of China (No. 60804032), the Central University Basic Research Foundation of South China University of Technology (No. 2009zm0178), and the Small Project Funding of HKU from HKU SPACE Research Fund (No. 201007176165).

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

Qing WANG,Tongke ZHONG,Ngai WONG,Qingyang WANG

(School of information Science and Technology, Sun Yat-Sen University; Department of Electrical and Electronic Engineering, The University of Hong Kong;School of Electric Power, South China University of Technology;College of Automation and Engineering, South China University of Technology)

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.

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