Trajectory Tracking for a Quadrotor System: A Flatness-based Nonlinear Predictive Control Approach

This paper proposes a flatness-based nonlinear predictive control strategy to solve the trajectory tracking problem for an underactuated quadrotor system model. It is shown that the present nonlinear model can be transformed to a controllable linear system on Brunovskys canonical form by using the differential flatness theory. Thus, a model predictive controller (MPC) is designed for the linear equivalent system to carry out trajectory tracking tasks. Since certain variables of the corresponding transformed system can not be measured directly, a state estimation is performed by a derivative-free Kalman filtering approach. The efficiency of the proposed control scheme is demonstrated through numerical simulations.