Model predictive control for path tracking of a VTOL tail-sitter UAV in an HIL simulation environment

This paper investigates the application of Model Predictive Control (MPC) for path tracking of a vertical takeoff and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hovering. In this work, the nonlinear dynamic model of a quad-rotor tail-sitter UAV including the aerodynamic effect of the wing, propellers, and slipstream was developed. The cascaded MPC controllers were then built upon linearized dynamic models. Path tracking simulations were conducted in a hardware-in-loop (HIL) environment where the UAV model and controllers were running on a PC and a flight computer independently. The simulation results show that the proposed MPC controllers are capable to perform good path tracking and the ability of disturbance rejection under limited on-board computation resource.