Data-Driven Model Reduction by Moment Matching for Linear Systems through a Swapped Interconnection

被引：0

作者：

Mao, Junyu ^{[1
]}

Scarciotti, Giordano ^{[1
]}

机构：

[1] Imperial Coll London, Dept Elect & Elect Engn, London SW7 2AZ, England

来源：

2022 EUROPEAN CONTROL CONFERENCE (ECC) | 2022年

关键词：

Model reduction; system identification; moment matching; data-driven; time-domain; swapped interconnection; linear systems; INTERPOLATION; APPROXIMATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this work, we propose a time-domain data-driven technique for model reduction by moment matching of linear systems. We propose an algorithm, based on the so-called swapped interconnection, that (asymptotically) approximates an arbitrary number of moments of the system from a single time-domain sample. A family of reduced-order models that match the estimated moments is derived. Finally, the use of the proposed algorithm is demonstrated on the problem of model reduction of a building model.

引用

页码：1690 / 1695

页数：6

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