This paper addresses the technology of active flow control for stabilizing a flow field. In order for flow field modeling from the control point of view, the huge-data set from CFD(computational fluid dynamics) are reduced by using a POD(Proper Orthogonal Decomposition) method. And then the flow field is expressed with dynamic equation by low-order modelling approach based on the time and frequency domain analysis. A neural network flow estimator from the pressure information measured on the surface is designed for the estimation of the flow state in the space. The closed-loop system is constructed with feedback flow controller for stabilizing the vortices on the flow field.