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A physics-based approach to flow control using system identification

Published online by Cambridge University Press:  07 June 2012

Aurelien Hervé ,
Denis Sipp ,
Peter J. Schmid  and
Manuel Samuelides
Aurelien Hervé
Affiliation:
ONERA - The French Aerospace Lab, 8 rue des Vertugardins, 92190 Meudon, France
Denis Sipp
Affiliation:
ONERA - The French Aerospace Lab, 8 rue des Vertugardins, 92190 Meudon, France
Peter J. Schmid*
Affiliation:
Laboratoire d’Hydrodynamique (LadHyX), CNRS-Ecole Polytechnique, 91128 Palaiseau, France
Manuel Samuelides
Affiliation:
ONERA - The French Aerospace Lab, 2 av. Edouard Belin, 31055 Toulouse, France
*
†Email address for correspondence: peter@ladhyx.polytechnique.fr
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Abstract

Control of amplifier flows poses a great challenge, since the influence of environmental noise sources and measurement contamination is a crucial component in the design of models and the subsequent performance of the controller. A model-based approach that makes a priori assumptions on the noise characteristics often yields unsatisfactory results when the true noise environment is different from the assumed one. An alternative approach is proposed that consists of a data-based system-identification technique for modelling the flow; it avoids the model-based shortcomings by directly incorporating noise influences into an auto-regressive (ARMAX) design. This technique is applied to flow over a backward-facing step, a typical example of a noise-amplifier flow. Physical insight into the specifics of the flow is used to interpret and tailor the various terms of the auto-regressive model. The designed compensator shows an impressive performance as well as a remarkable robustness to increased noise levels and to off-design operating conditions. Owing to its reliance on only time-sequences of observable data, the proposed technique should be attractive in the design of control strategies directly from experimental data and should result in effective compensators that maintain performance in a realistic disturbance environment.

JFM classification

Flow Control: Flow Control

Information

Type
Papers
Information
Journal of Fluid Mechanics , Volume 702 , 10 July 2012 , pp. 26 - 58
Copyright
Copyright © Cambridge University Press 2012

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