空气中空化流动负反馈控制降阶模型的建立检测方案(粒子图像测速)

Controlling the flow over aerodynamic bodies has been a challenging problem for many years. Different open loop control techniques have been used in several flow configurations with some degree of success. However, in most cases the effectiveness of the controller is limited to the design conditions. In the present work, Proper Orthogonal Decomposition (POD) is used to derive low dimensional models of the subsonic flow over a cavity, in an effort to develop a feedback control system that can control the characteristic of the flow field. The Galerkin method is used as an additional tool to capture the time evolution of the flow field, reducing the problem into a system of ordinary differential. The stochastic estimation method is then used to link the variables that can be physically measured with those involved in the model. Particle Image Velocimetry (PIV) data and surface pressure measurement for the unforced flow (baseline) and for several open loop forcing conditions are used to derive the models.