Robust hybrid nonlinear control systems for the dynamics of a quadcopter drone

Robustness in the face of uncertainties is an important aspect in designing high performance control systems. This paper addresses the problem of accurate trajectory tracking of a small quadcopter unmanned aerial vehicle in the face of uncertainties. Accommodating the worst-case scenario, we propose a hybrid feedback and feedforward autopilot that has the capability to eliminate the cross-coupling disturbance between the lateral and the longitudinal loops with respect to the vertical loop as well as external disturbances (e.g., wind gusts). The proposed control system leverages on the technical benefits of both the nonlinear model predictive control and the fuzzy feedforward compensator. We highlight the efficacy of our hybrid autopilot system with respect to the performance of the conventional PD control systems through rigorous comparative studies. We also present stability analysis of our hybrid control system.