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Journal of Shanghai University >

2021 , Vol. 27 >Issue 1: 59 - 77

DOI: https://doi.org/10.12066/j.issn.1007-2861.2114

Research Articles

Model reduction of linear fast periodically switched systems using balanced truncation

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  • 1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China
    2. Computer Center, Shanghai University, Shanghai, 200444, China

Received date: 2018-12-26

  Online published: 2021-02-28

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Abstract

This study examines the model order reduction of linear fast periodically switched systems within the framework of a balanced truncation approach. The direct current (DC) averaged state-space model is introduced to describe the averaged dynamics of the given periodically switched systems in the presence of a DC input signal. In addition, a balanced truncation-based algorithm is developed to generate the desired reduced periodically switched model. A small-signal averaged state-space model is introduced to deal with cases in which the alternating current input signal is included. Similarly, an algorithm to generate the desired reduced model is proposed by exploiting the singular perturbation-type balanced truncation. Finally, numerical and experimental examples are presented to illustrate the effectiveness of the proposed results.

Key words： model reduction; periodically switched system; averaged model; small-signal average model; balanced truncation

Cite this article

DU Xin, HU Zheng, WANG Jianying . Model reduction of linear fast periodically switched systems using balanced truncation[J]. Journal of Shanghai University, 2021 , 27(1) : 59 -77 . DOI: 10.12066/j.issn.1007-2861.2114

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