Flight Envelope Predicting Algorithm for UAV Based on UKF
Shumin Lu, Mou Chen, Mingsuo Li · 2019
In this paper, the Envelope Prediction Algorithm (EPA) is presented based on the Unscented Kalman Filter (UKF) method for the Unmanned Aerial Vehicle (UAV). Firstly, the flight envelope of UAV extended system is calculated by the Attainable Equilibrium Set (AES) algorithm. The discrete Newton iteration method is used to solve the nonlinear algebraic equation of UAV, and then the AES is obtained at the current state. Secondly, the UKF has the characteristics of high accuracy and strong stability, which can effectively to predict the next moment state value of the nonlinear system. Therefore, the UKF in this paper is used to predict the state variables of the UAV system at the next moment. Finally, the AES algorithm is adopted to calculate the next moment flight envelope of the UAV. The simulation results of the UAV indicate that the EPA algorithm can effectively predict the next moment AES of the UAV based on the predict the results.