Model Predictive Controller for Quadcopter Trajectory Tracking Based on Feedback Linearization

In this study, a feedback linearization model predictive control algorithm is designed for quadcopter trajectory tracking. By applying feedback linearization to the quadcopter nonlinear model, the quadcopter nonlinear model is transformed into a linear system as the foundation for further controller design. By feedback linearization, the linear control schemes can be used to control the quadcopter. A model predictive controller is then designed for the linearized quadcopter model without considering the external disturbance. A disturbance observer is designed to estimate the external disturbance, keeping the estimation error BIBO stable to compensate for the external disturbance. Numerical simulations are performed to evaluate the proposed control algorithm. The simulations are performed in two test scenarios to examine the tracking performance. The quadcopter is commended for reaching a waypoint (scenario. I) and tracking a helical trajectory (scenario. II) in the simulations, and the root means square errors are calculated to demonstrate the tracking effectiveness. The simulation results show that the designed control algorithm can effectively ensure the quadcopter tracks a given trajectory under constant or continuous disturbances.