論文

査読有り
2016年

Optimality of simulation-based nonlinear model reduction: Stochastic controllability perspective

2016 AMERICAN CONTROL CONFERENCE (ACC)
  • Kenji Kashima

開始ページ
7243
終了ページ
7248
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/ACC.2016.7526816
出版者・発行元
IEEE

The practical applicability of control theoretic model reduction methods is still limited to linear middle-scale systems. This shows a clear contrast to the Proper Orthogonal Decomposition (POD), which is a simulation-based model reduction method that has been widely applied to nonlinear large-scale systems, but with no theoretical underpinnings for its application to controlled systems. In this paper, we show that these controllability-based and simulation-based methodologies are equivalent when the input port is open to a noisy environment.

リンク情報
DOI
https://doi.org/10.1109/ACC.2016.7526816
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000388376107051&DestApp=WOS_CPL
ID情報
  • DOI : 10.1109/ACC.2016.7526816
  • ISSN : 0743-1619
  • Web of Science ID : WOS:000388376107051

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