A Structured Model Reduction Method for Linear Interconnected Systems

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Abstract

This paper develops a model reduction method for a large-scale interconnected system that consists oflinear dynamic components. In the model reduction, we aim to preserve physical characteristics of each component. To this end, we formulate a structured model reduction problem that reduces the model order of components while preserving the feedback structure. Although there are a few conventional methods for such structured model reduction to preserve stability, they do not explicitly consider performance of the reduced-order feedback system. One of the difficulties in the problem with performance guarantee comes from nonlinearity of a feedback system to each component. The problem is essentially in a class of nonlinear optimization problems, and therefore it cannot be efficiently solved even in numerical computation. In this paper, application of an equivalent transformation and a proper approximation reduces this nonlinear problem to a problem of the weighted linear model reduction. Then, by using the weighted balanced truncation technique, we construct a reduced-order model with preserving the feedback structure to ensure small modeling error. Finally, we verify the effectiveness of the proposed method through numerical experiments.

Original languageEnglish
Article number012108
JournalJournal of Physics: Conference Series
Volume744
Issue number1
DOIs
Publication statusPublished - 2016 Oct 3

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linear systems
preserving
approximation
nonlinearity
optimization

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

A Structured Model Reduction Method for Linear Interconnected Systems. / Sato, Ryo; Inoue, Masaki; Adachi, Shuichi.

In: Journal of Physics: Conference Series, Vol. 744, No. 1, 012108, 03.10.2016.

Research output: Contribution to journalArticle

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