Minimum time trajectory optimization of a tail-sitter aerial vehicle using nonlinear programming

Aerial tail-sitters have drawn many attentions in recent years. The main challenge of employing these vehicles is to ensure safe and efficient takeoff and landing. The aim of the current study is to develop a gradient-base optimization algorithm for a jet aerial tail-sitter in order to obtain minimum time trajectories in transition flight phases. The vehicle is supposed to utilize thrust vectoring system instead of conventional control surfaces that will pose minimal drawbacks in terms of low speed efficiency and complexity. The time-optimal trajectories are computed using the nonlinear dynamic equations of motion of the vehicle in order to make sure that the vehicle can follow the optimum trajectory. The results show that although the tail-sitter is unstable in low speed transition flight conditions, the optimal control can guide it to the desired condition in minimum time.