The automatic optimization of flow control devices is a delicate issue, due to the drastic computational time related to unsteady high-fidelity flow analyses and the possible multimodality of the objective function. Thus, we experiment in this article the use of kriging-based algorithms to optimize flow control parameters, since these methods have shown their efficiency for global optimization at moderate cost. Navier-Stokes simulations, carried out for different control parameters, are used to build iteratively a kriging model. At each step, a statistical analysis is performed to enrich the model with new simulation results by exploring the most promising areas, until optimal flow control parameters are found. This approach is validated and demonstrated on two problems, including comparisons with similar studies: the control of the flow around an oscillatory rotating cylinder and the reduction of the intensity of a shock wave for a transonic airfoil by adding a bump to the airfoil profile.