Online Trajectory Optimization for UAV in Uncertain Environment

The stability of the flight attitude and the rationality of the path are two critical indicators to measure the application of the UAV. Especially for the Unmanned Aerial Vehicle (UAV), the stability of attitude, and the yaw angle without external interference play a vital role in the whole UAV system. Some reasons can have an influence on the performance of the UAV; one is the problem of trajectory tracking; another is uncertain in the environment, the UAV model will be vulnerable to external disturbances; therefore, a new nonlinear back-step slide mode controller combined with the extended Kalman filter-simultaneous localization and mapping (EKF-SLAM) algorithm and hp adaptive pseudo-spectral algorithm is proposed to estimate the uncertain disturbances and to realize the online optimization in the actual trajectory of the UAV. Computer simulations are presented to show how the proposed method works. The UAV principles are determined, and the nonlinear motion mathematical model of the UAV is established. The experimental data are analyzed to prove the correctness of the theoretical analysis.