The performance of active control of vortex shedding from a circular cylinder is studied experimentally with rotational feedback oscillations. The optimization of the control parameters, such as the phase lag, the feedback gain, and the position of reference sensor are carried out using neural networks to minimize the reference velocity fluctuations in the cylinder wake. Measurement of pressure distributions over the circular cylinder under the optimum control indicate that the drag force is reduced by 16% and the lift force is suppressed by more than 70% in comparison with the stationary cylinder.
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