The invention provides a wind tunnel experiment-based wing high-
attack-angle flow separation combined
intelligent control method, which comprises the following steps of: arranging active flow control devices at 10% chord length and
trailing edge flap of a wing to inhibit wing high-
attack-angle flow separation; the active flow control device at the 10% chord length of the wing adopts direct
jet flow, the
jet flow direction is perpendicular to the chord line of the wing, three
jet flow exciters are uniformly arranged along the spanwise direction, the active flow control device at the
trailing edge flap adopts sweeping jet flow, the jet flow direction is parallel to the surface of the wing at the position, and 18 sweeping jet flow actuators are uniformly arranged along the spanwise direction; the jet flow of the two sets of flow control devices is adjusted through corresponding
mass flow controllers, jet flow
momentum distribution is dynamically optimized in combination with a
reinforcement learning algorithm, the lift coefficient is remarkably increased, and
energy consumption is reduced. The flow field state is fed back in real time through a pressure measuring
system and a force measuring
system, a closed-
loop control system is constructed, and an execution action is output according to the flow field information around the wing to control an active flow control device arranged on the wing so as to inhibit flow separation on the surface of the wing, so that the wing gets rid of the stall state and the lift force is improved.