EconPapers    
Economics at your fingertips  
 

Dimension reduction for second-order systems by general orthogonal polynomials

Zhi-Hua Xiao and Yao-Lin Jiang

Mathematical and Computer Modelling of Dynamical Systems, 2014, vol. 20, issue 4, 414-432

Abstract: In this article, we discuss the time-domain dimension reduction methods for second-order systems by general orthogonal polynomials, and present a structure-preserving dimension reduction method for second-order systems. The resulting reduced systems not only preserve the second-order structure but also guarantee the stability under certain conditions. The error estimate of the reduced models is also given. The effectiveness of the proposed methods is demonstrated by three test examples.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/13873954.2013.867274 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:nmcmxx:v:20:y:2014:i:4:p:414-432

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/NMCM20

DOI: 10.1080/13873954.2013.867274

Access Statistics for this article

Mathematical and Computer Modelling of Dynamical Systems is currently edited by I. Troch

More articles in Mathematical and Computer Modelling of Dynamical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:nmcmxx:v:20:y:2014:i:4:p:414-432