LAUSR

Abstract Model predictive control (MPC) of a separated flow around a circular cylinder at a low Reynolds number is presented in this paper. In order to reduce online computational cost, we propose to extract an explicit control law from data obtained by a number of offline simulations of the closed-loop system under MPC. The Gaussian process regression is employed to extract a control law. The effectiveness of the obtained control law is verified by a numerical simulation. Although the control law uses information about the flow on the surface of the cylinder, flow separation and vortex shedding are successfully mitigated. Moreover, improvement of aerodynamic performances is also observed.