Real-time Maneuver Command Generation and Tracking For a Miniature Fixed-Wing Drone with a Ducted-Fan Unit
Su Qun Cao, Xiangke Wang, Huangchao Yu · 2021 60th IEEE Conference on Decision and Control (CDC) · 2021
Due to the limitations of actuators, physical components, and onboard computers, autonomously performing aggressive maneuvers is challenging for miniature fixed-wing unmanned aerial vehicles(UAVs), especially for one with a ducted fan. This paper proposed an integrated maneuver command generation and tracking control(MCGTC) scheme that enables fixed-wing UAVs to finish agile acrobatics. Our algorithm has two essential parts: 1)A maneuver command generator learned from a few demonstrations. The geometric characteristics of the pilot’s demonstrated trajectories are preserved through a new, coordinate-free invariant paradigm. 2)A tracking control structure consists of an incremental dynamic inversion(INDI) based airspeed controller and a nonlinear dynamic inversion(NDI) based attitude controller. The feasibility and effectiveness of our proposed MCGTC scheme are verified through flight tests. Using a 2.5kg fixed-wing drone with a 70mm ducted fan, we can realize an agile Immelman maneuver in the physical world.