Robust Control Strategy for Quadcopters using Sliding Mode Control and Model Predictive Control

Abstract

In this paper, a robust model predictive control strategy for quadcopters is proposed. A sliding mode controller is developed that can stabilize and track reference attitude and altitude under modeling errors and external disturbances. A model predictive controller is developed that synthesizes two virtual control inputs for reference trajectory tracking in the inertial $x-y$ plane. To this end, a constrained optimization problem is solved wherein the virtual inputs are constrained such that feasible reference values in roll and pitch angles exist. Two illustrative simulation examples are included to demonstrate the effectiveness of the proposed control strategy. The performance of the proposed controller is compared with the performances of a nonlinear model predictive controller (NMPC) and an integral backstepping (IB) controller. It is shown that the proposed controller is able to achieve robust trajectory tracking under modeling errors and external disturbances, and has a better position tracking performance compared to the NMPC and IB controllers.