| Issue |
MATEC Web Conf.
Volume 286, 2019
14th Congress of Mechanics (CMM2019)
|
|
|---|---|---|
| Article Number | 07013 | |
| Number of page(s) | 3 | |
| Section | Fluid Mechanics, Rheology, Modeling, Instabilities and Transition | |
| DOI | https://doi.org/10.1051/matecconf/201928607013 | |
| Published online | 14 August 2019 | |
Data assimilation for control of a plane mixing layer
Institut Pprime, CNRS – Université de Poitiers – ISAE-ENSMA, UPR 3346, 11 Boulevard Marie et Pierre Curie, BP 30179, F86962 Futuroscope Chasseneuil Cedex, France
* Corresponding author: nishant.kumar@cnrs.pprime.fr
The design of active model-based flow controllers requires the knowledge of a dynamical model of the flow. However, real-time and robust estimation of the flow state remains a challenging task when only limited spatial and temporal discrete measurements are available. In this study, the objective is to draw upon the methodologies implemented in meteorology to develop dynamic observers for flow control applications. Well established data assimilation (DA) method using Kalman filter is considered. These approaches are extended to both estimate model states and parameters. Simple non-linear dynamical models are first considered to establish quantitative comparisons between the different algorithms. An experimental demonstration for the particular case of a plane mixing layer is then proposed.
Key words: data assimilation / active flow control / plane mixing layer
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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