![]() ![]() The consideration of the time delay of the observations did not improve the accuracy of the estimation. ![]() Generating or exporting a database cannot be specified through the. The main purpose of this input structure is to allow native interface with MachUpX. The analysis showed that the coefficients of the observation error covariance matrix, which is a hyperparameter of the Kalman filter, and the number of POD modes to be estimated contribute to the accuracy of the estimation. This object describes the geometry of the airfoil, the trailing flap (if present), and how its aerodynamics are to be predicted, whether using linear predictions, a database, or polynomial fits. We also propose a nonlinear state-space model as a state-space representation, which is an improvement of the conventional linear state-space model, and perform estimation using an extended Kalman filter, and investigate the estimation accuracy in the same way. In this study, we aim to improve the estimation accuracy of the method based on the Kalman filter and to investigate the effects of the Kalman filter hyperparameters, the number of POD modes to be estimated, and the time delay of the observations on the accuracy of the flow field estimation, based on wind tunnel test data. The method estimates a low-dimensional flow field represented by proper orthogonal decomposition (POD) modes with a Kalman filter. A low-dimensional flow field is estimated from unsteady pressure sensors data that can be attached to the airfoil surface, for feedback control of the flow field around an airfoil. 11/9/96 - Posted some new airfoils to the Airfoil Data Site: bw3.dat, daviscorrected.dat, e231.dat, e476.dat, e477.dat, e478.dat, eh0009.dat, eh1090. ![]()
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