2016年
Optimality of simulation-based nonlinear model reduction: Stochastic controllability perspective
2016 AMERICAN CONTROL CONFERENCE (ACC)
- 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
- ID情報
-
- DOI : 10.1109/ACC.2016.7526816
- ISSN : 0743-1619
- Web of Science ID : WOS:000388376107051