Adaptive quaternion control of a miniature tailsitter UAV

The miniature tailsitter is a unique aircraft with inherent advantages over typical unmanned aerial vehicles. With the capabilities of both hover and level flight, these small, portable systems can produce efficient maneuvers for enhanced surveillance and autonomy with little threat to surroundings and the system itself. Such vehicles create control challenges due to the two different flight regimes. These challenges are addressed with a computationally efficient adaptive quaternion control algorithm. A backstepping method for model cancellation and consistent tracking of reference model attitude dynamics is derived. This is used in conjunction with a regularized data-weighting recursive least-squares algorithm for the on-line identification of system parameters. Simulation and hardware results are presented as validation of the technique.