Development and Implementation of an Experimental-Based Reduced-Order Model for Feedback Control of Subsonic Cavity Flows

2007 ◽  
Vol 129 (7) ◽  
pp. 813-824 ◽  
Author(s):  
E. Caraballo ◽  
J. Little ◽  
M. Debiasi ◽  
M. Samimy
Keyword(s):  
Experimental Data ◽  
Feedback Control ◽  
Real Time ◽  
Surface Pressure ◽  
Reduced Order Model ◽  
Estimation Methods ◽  
Cavity Flows ◽  
Pressure Measurements ◽  
Order Model ◽  
Reduced Order

This work is focused on the development of a reduced-order model based on experimental data for the design of feedback control for subsonic cavity flows. The model is derived by applying the proper orthogonal decomposition (POD) in conjunction with the Galerkin projection of the Navier-Stokes equations onto the resulting spatial eigenfunctions. The experimental data consist of sets of 1000 simultaneous particle image velocimetry (PIV) images and surface pressure measurements taken in the Gas Dynamics and Turbulent Laboratory (GDTL) subsonic cavity flow facility at the Ohio State University. Models are derived for various individual flow conditions as well as for their combinations. The POD modes of the combined cases show some of the characteristics of the sets used. Flow reconstructions with 30 modes show good agreement with experimental PIV data. For control design, four modes capture the main features of the flow. The reduced-order model consists of a system of nonlinear ordinary differential equations for the modal amplitudes where the control input appears explicitly. Linear and quadratic stochastic estimation methods are used for real-time estimation of the modal amplitudes from real-time surface pressure measurements.

Feedback control of subsonic cavity flows using reduced-order models

2007 ◽  
Vol 579 ◽  
pp. 315-346 ◽  
Author(s):  
M. SAMIMY ◽  
M. DEBIASI ◽  
E. CARABALLO ◽  
A. SERRANI ◽  
X. YUAN ◽  
...  
Keyword(s):  
Feedback Control ◽  
Surface Pressure ◽  
Controller Design ◽  
Cavity Flow ◽  
Open Loop ◽  
Reduced Order Model ◽  
Cavity Flows ◽  
Reduced Order Models ◽  
Order Model ◽  
Reduced Order

Development, experimental implementation, and the results of reduced-order model based feedback control of subsonic shallow cavity flows are presented and discussed. Particle image velocimetry (PIV) data and the proper orthogonal decomposition (POD) technique are used to extract the most energetic flow features or POD eigenmodes. The Galerkin projection of the Navier–Stokes equations onto these modes is used to derive a set of nonlinear ordinary differential equations, which govern the time evolution of the eigenmodes, for the controller design. Stochastic estimation is used to correlate surface pressure data with flow-field data and dynamic surface pressure measurements are used to estimate the state of the flow. Five sets of PIV snapshots of a Mach 0.3 cavity flow with a Reynolds number of 105 based on the cavity depth are used to derive five different reduced-order models for the controller design. One model uses only the snapshots from the baseline (unforced) flow while the other four models each use snapshots from the baseline flow combined with snapshots from an open-loop sinusoidal forcing case. Linear-quadratic optimal controllers based on these models are designed to reduce cavity flow resonance and are evaluated experimentally. The results obtained with feedback control show a significant attenuation of the resonant tone and a redistribution of the energy into other modes with smaller energy levels in both the flow and surface pressure spectra. This constitutes a significant improvement in comparison with the results obtained using open-loop forcing. These results affirm that reduced-order model based feedback control represents a formidable alternative to open-loop strategies in cavity flow control problems even in its current state of infancy.

Feedback Control of Cavity Flow Using Experimental Based Reduced Order Model

2005 ◽  
Author(s):  
Edgar Caraballo ◽  
X. Yuan ◽  
Jesse Little ◽  
Marco Debiasi ◽  
P Yan ◽  
...  
Keyword(s):  
Feedback Control ◽  
Cavity Flow ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order

scholarly journals Correction: Persoons, T.; Cressall, R.; Alimohammadi, S. Validating a Reduced-Order Model for Synthetic Jet Actuators Using CFD and Experimental Data. Actuators 2018, 7, 67

Actuators ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 16
Author(s):  
Tim Persoons ◽  
Rick Cressall ◽  
Sajad Alimohammadi
Keyword(s):  
Experimental Data ◽  
Synthetic Jet ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Synthetic Jet Actuators ◽  
Jet Actuators

The authors wish to make the following corrections to this paper [...]

Distributed Feedback Control of the Benjamin-Bona-Mahony-Burgers Equation by a Reduced-Order Model

2015 ◽  
Vol 5 (1) ◽  
pp. 61-74 ◽  
Author(s):  
Guang-Ri Piao ◽  
Hyung-Chun Lee
Keyword(s):  
Feedback Control ◽  
Numerical Experiments ◽  
Burgers Equation ◽  
Distributed Feedback ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Order Case ◽  
Functional Gain ◽  
Proper Orthogonal

AbstractA reduced-order model for distributed feedback control of the Benjamin-Bona-Mahony-Burgers (BBMB) equation is discussed. To retain more information in our model, we first calculate the functional gain in the full-order case, and then invoke the proper orthogonal decomposition (POD) method to design a low-order controller and thereby reduce the order of the model. Numerical experiments demonstrate that a solution of the reduced-order model performs well in comparison with a solution for the full-order description.

scholarly journals A Reduced-order Model for Real-time NMPC of Ethanol Steam Reformers

2021 ◽  
Vol 54 (3) ◽  
pp. 103-108
Author(s):  
Pedro Reyero ◽  
Xinwei Yu ◽  
Carlos Ocampo-Martinez ◽  
Richard D. Braatz
Keyword(s):  
Real Time ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Steam Reformers ◽  
Ethanol Steam

scholarly journals Reduced-order model based feedback control of the modified Hasegawa-Wakatani model

2013 ◽  
Vol 20 (4) ◽  
pp. 042501 ◽  
Author(s):  
I. R. Goumiri ◽  
C. W. Rowley ◽  
Z. Ma ◽  
D. A. Gates ◽  
J. A. Krommes ◽  
...  
Keyword(s):  
Feedback Control ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Model Based
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