CRUISE FLIGHT PARAMETERS PREDICTION BASED ON ADAPTIVE AR MODEL
In order to realize the trend prediction of flight parameters more accurately,a stable cruise flight parameter prediction method based on adaptive auto regressive(AR)model is proposed.According to the screening conditions of stable cruise parameters,the flight parameters required for modeling were obtained.The parameters of AR model were estimated by Kalman filter principle,and the system equations were constructed with flight parameters.The parameters of AR model were updated and modified by unscented Kalman filter(UKF)in real time.The predicted values of adaptive AR model were compared with those of curve fitting model and grey model.The data samples of Boeing B777-300ER quick aircraft recorder(QAR)were used for simulation verification.The results show that the adaptive AR model is better in data prediction accuracy and convergence rate,which can effectively reduce the accuracy error of prediction model with the increase of steps and improve the accuracy of parameter prediction.This research is of great significance in aircraft maintenance support,condition monitoring and prediction.
Unscented Kalman filterAdaptive AR modelFlight parameter predictionCurve fitting modelGrey model
国家科技期刊平台
NSTL
万方数据
维普
