To prevent aircraft from entering dangerous state under unsteady aerodynamics,the state prediction by modeling is im-portant means to ensure flight safety.Traditional methods have complex modeling processes,high engineering difficulty,and weak universality.To better solve the prediction of flight status at high angle of attack,a time series prediction method based on deep learning was used to infer the flight status of the aircraft,thereby achieving the goal of maximizing aircraft performance and ensuring the flight safety.A multi task Transformer model was proposed to simultaneously perform flight state parameter regression and flight state classification.Through experiments,compared to similar models,the predictive performance of this model is significantly improved.
关键词
多任务/深度学习/时序预测/状态分类/气动力建模/大迎角/非定常气动力
Key words
multi-task/deep learning/sequence prediction/statement classify/aerodynamic modeling/high angle of attack/unsteady aerodynamic
维普
万方数据