Reduced order models for boundary feedback flow control

2008 ◽  
Author(s):  
Seddik M. Djouadi ◽  
R.C. Camphouse ◽  
J.H. Myatt
Keyword(s):  
Flow Control ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Boundary Feedback

Reduced Order Models for Optimal Flow Control

PAMM ◽  
2021 ◽  
Vol 20 (S1) ◽  
Author(s):  
Maria Strazzullo ◽  
Francesco Ballarin ◽  
Gianluigi Rozza
Keyword(s):  
Flow Control ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Optimal Flow ◽  
Optimal Flow Control

Anisothermal Flow Control by Using Reduced-Order Models

2012 ◽  
Author(s):  
Alexandra Tallet ◽  
Cédric Leblond ◽  
Cyrille Allery
Keyword(s):  
Fluid Flow ◽  
Flow Control ◽  
Projection Method ◽  
Control Strategies ◽  
Pollutant Concentration ◽  
Galerkin Projection ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Optimal Projection ◽  
Fluid Flow Control

Despite constantly improving computer capabilities, classical numerical methods (DNS, LES,…) are still out of reach in fluid flow control strategies. To make this problem tractable almost in real-time, reduced-order models are used here. The spatial basis is obtained by POD (Proper Orthogonal Decomposition), which is the most commonly used technique in fluid mechanics. The advantage of the POD basis is its energetic optimality: few modes contain almost the totality of energy. The ROM is achieved with the recent developed optimal projection [1], unlike classical methods which use Galerkin projection. This projection method is based on the minimization of the residual equations in order to have a stabilizing effect. It enables moreover to access pressure field. Here, the projection method is slightly different from [1]: a formulation without the Poisson equation is proposed and developed. Then, the ROM obtained by optimal projection is introduced within an optimal control loop. The flow control strategy is illustrated on an isothermal square lid-driven cavity and an anisothermal square ventilated cavity. The aim is to reach a target temperature (or target pollutant concentration) in the cavity, with an interior initial temperature (or initial pollutant concentration), by adjusting the inlet fluid flow rate.

Reduced-order models for flow control: balanced models and Koopman modes

2009 ◽  
pp. 43-50 ◽  
Author(s):  
Clarence W. Rowley ◽  
Igor Mezić ◽  
Shervin Bagheri ◽  
Philipp Schlatter ◽  
Dan S. Henningson
Keyword(s):  
Flow Control ◽  
Reduced Order Models ◽  
Reduced Order

Reduced Order Nonlinear Navier-Stokes Models for Synthetic Jets

2002 ◽  
Vol 124 (2) ◽  
pp. 433-443 ◽  
Author(s):  
Othon K. Rediniotis ◽  
Jeonghwan Ko ◽  
Andrew J. Kurdila
Keyword(s):  
Flow Control ◽  
Numerical Study ◽  
Control Strategies ◽  
Order Reduction ◽  
Synthetic Jet ◽  
Reduced Order Models ◽  
Loop Control ◽  
Reduced Order ◽  
Synthetic Jet Actuators ◽  
Jet Actuators

While the potential for the use of synthetic jet actuators to achieve flow control has been noted for some time, most of such flow control studies have been empirical or experimental in nature. Several technical issues must be resolved to achieve rigorous, model-based, closed-loop control methodologies for this class of actuators. The goal of this paper is consequently two-fold. First, we seek to derive and evaluate model order reduction methods based on proper orthogonal decomposition that are suitable for synthetic jet actuators. Second, we seek to derive rigorously stable feedback control laws for the derived reduced order models. The realizability of the control strategies is discussed, and a numerical study of the effectiveness of the reduced order models for two-dimensional flow near the jet exit is summarized.

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