Robust Model Predictive Control with ESO for Quadrotor Trajectory Tracking with Disturbances

In this paper, we propose a robust control algorithm for the quadrotor trajectory tracking under operating constraints and disturbances. The control strategy consists of two serial connected controllers by integrating model predictive control (MPC) with active disturbance rejection control (ADRC). We first design a kinematic controller based on MPC and exploit constraints tightening method to guarantee robust constraints satisfaction. The optimal velocity obtained by the MPC optimization problem is set to be the desired velocity of the dynamic controller. To track the desired velocity, a dynamic controller is designed by utilizing an extended state observer (ESO) to actively reject the disturbances caused by external noises and model uncertainties. The whole system is proved to be stable and feasible. Finally, an illustrative example is provided to verify the efficiency and robustness of the proposed robust tracking control strategy.