Application of low-dimensional techniques for closed-loop control of turbulent flows

Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Mechanical and Aerospace Engineering


Low-dimensional techniques, Stochastic estimation, Experimental closed-loop, POD, Proper orthogonal decomposition, Closed-loop control

Subject Categories

Aerospace Engineering | Engineering | Mechanical Engineering


The groundwork for an advanced closed-loop control of separated shear layer flows is laid out in this document. The experimental testbed for the present investigation is the turbulent flow over a NACA-4412 model airfoil tested in the Syracuse University subsonic wind tunnel at Re =135,000. The specified control objective is to delay separation - or stall - by constantly keeping the flow attached to the surface of the wing. The proper orthogonal decomposition (POD) is shown to he a valuable tool to provide a low-dimensional estimate of the flow state and the first POD expansion coefficient is proposed to he used as the control variable. Other reduced-order techniques such as the modified linear and quadratic stochastic measurement methods (mLSM, mQSM) are applied to reduce the complexity of the flow field and their ability to accurately estimate the flow state from surface pressure measurements alone is examined. A simple proportional feedback control is successfully implemented in real-time using these tools and flow separation is efficiently delayed by over 3 degrees angle of attack. To further improve the quality of the flow state estimate, the implementation of a Kalman filter is foreseen, in which the knowledge of the flow dynamics is added to the computation of the control variable to correct for the potential measurement errors. To this aim, a reduced-order model (ROM) of the flow is developed using the least-squares method to obtain the coefficients of the POD/Galerkin projection of the Navier-Stokes equations from experimental data. To build the training ensemble needed in this experimental procedure, the spectral mLSM is performed to generate time-resolved series of POD expansion coefficients from which temporal derivatives are computed. This technique, which is applied to independent PIV velocity snapshots and time-resolved surface measurements, is able to retrieve the rational temporal evolution of the flow physics in the entire 2-D measurement area. The quality of the spectral measurements is confirmed by the results from both the linear and quadratic dynamical systems. The preliminary results from the linear ROM strengthens the motivation for future control implementation of a linear Kalman filter in this flow.


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