Real-Time Feedback Control of Flow-Induced Cavity Tones

A generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The control algorithm demonstrated multiple Rossiter-mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are collocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible with the present sensor/actuator arrangement. In the control-algorithm development, the cavity dynamics were treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support to that treatment

Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach

The final publication is available at Springer via http://dx.doi.org/10.1007/s00348-015-2107-3The potential benefits of active flow control are no more debated. Among many others applications, flow control provides an effective mean for manipulating turbulent separated flows. Here, a nonthermal surface plasma discharge (dielectric barrier discharge) is installed at the step corner of a backward-facing step (U0 = 15 m/s, Reh = 30,000, Re¿ = 1650). Wall pressure sensors are used to estimate the reattaching location downstream of the step (objective function #1) and also to measure the wall pressure fluctuation coefficients (objective function #2). An autonomous multi-variable optimization by genetic algorithm is implemented in an experiment for optimizing simultaneously the voltage amplitude, the burst frequency and the duty cycle of the high-voltage signal producing the surface plasma discharge. The single-objective optimization problems concern alternatively the minimization of the objective function #1 and the maximization of the objective function #2. The present paper demonstrates that when coupled with the plasma actuator and the wall pressure sensors, the genetic algorithm can find the optimum forcing conditions in only a few generations. At the end of the iterative search process, the minimum reattaching position is achieved by forcing the flow at the shear layer mode where a large spreading rate is obtained by increasing the periodicity of the vortex street and by enhancing the vortex pairing process. The objective function #2 is maximized for an actuation at half the shear layer mode. In this specific forcing mode, time-resolved PIV shows that the vortex pairing is reduced and that the strong fluctuations of the wall pressure coefficients result from the periodic passages of flow structures whose size corresponds to the height of the step model.Peer ReviewedPostprint (author's final draft

Variable structure model for flow-induced tonal noise control with plasma actuators

The objective of this work was to study the effect of plasma actuators in attenuating low-speed flow-induced cavitytones from a control point of view by employing techniques from classical control. A modification of the existingphysics-based linear model produced a new variable structure model in which a plasma actuator was regarded as alinear gain. The parameters of the overall model working at two operating voltages were identified usingexperimental data. The effects of the plasma actuator control at other various operating voltages were thus able to bepredicted using linear interpolation. The good agreement between the predicted and the measured data supportedthe proposed variable structure model, inside of which plasma actuators affected the damping of cavity pressureoscillations proportionally to the applied voltage to reduce flow-induced tonal noise. With the proposed variablestructure model the system stability controlled by plasma actuators at various operating voltages was ensured, thus aclosed-loop control method could be applied without leading to instability. A simple proportional integral derivativecontroller was implemented. Results show the potential of a closed-loop method by increasing system powerefficiency

Aiaa 2002---3158

this paper. Adaptive system identication algorithms were applied to an experimental cavity-ow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated 7dB tone reductions at multiple frequencies. Several di#erent adaptive system identication algorithms were applied at a single freestream Mach number of 0.275. Adaptive nite- impulse response (FIR) lters of orders up to N = 100 were found to be unsuitable for modeling the cavity ow dynamics. Adaptive innite-impulse response (IIR) lters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive lter coe#cients. Given the sample-time requirements imposed by the cavity ow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time contro

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control