Model Predictive Control Based on ILQR for Tilt-Propulsion UAV

Abstract

The transition flight of tilt-propulsion UAV is a complex and time-varying process, which leads to great challenges in the design of a stable and robust controller. This work presents a unified model predictive controller, which can handle the full envelope from vertical take-off and landing to cruise flight, to mean that the UAV can achieve a near-optimal transition flight under uncertainty conditions. Firstly, the nonlinear dynamic model of the tilt-propulsion UAV is developed, in which the aerodynamic/propulsion coupling effect of the ducted propeller is considered. Then, a control framework, including global trajectory planning and finite horizon control, is designed. Taking the planned global trajectory as the reference input, a controller is proposed with an inner layer based on ILQR optimization and an outer layer based on feedback correction and forward rolling of the MPC frame. The ILQR-MPC controller has high computational efficiency to deal with nonlinear problems, and has the ability to give full play to UAV’s control ability and suppress uncertainty. Finally, the simulation results show that ILQR-MPC controller obviously performs better than the ILQR feedforward controller, and gains a scheduling PID controller and MPC controller.