Multi-order Arnoldi-based model order reduction of second-order time-delay systems

Zhi-Hua Xiao and Yao-Lin Jiang

International Journal of Systems Science, 2016, vol. 47, issue 12, 2925-2934

Abstract: In this paper, we discuss the Krylov subspace-based model order reduction methods of second-order systems with time delays, and present two structure-preserving methods for model order reduction of these second-order systems, which avoid to convert the second-order systems into first-order ones. One method is based on a Krylov subspace by using the Taylor series expansion, the other method is based on the Laguerre series expansion. These two methods are used in the multi-order Arnoldi algorithm to construct the projection matrices. The resulting reduced models can not only preserve the structure of the original systems, but also can match a certain number of approximate moments or Laguerre expansion coefficients. The effectiveness of the proposed methods is demonstrated by two numerical examples.

Date: 2016
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DOI: 10.1080/00207721.2015.1042087

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