Trajectory Control of a Delivery Quadcopter Using Self-Tuning Fuzzy-PID and Extended Kalman Filter

Abstract

Quadcopter is a very popular technology because it is flexible in movement and has high maneuverability. However, Quadcopter has challenges in maintaining flight stability and trajectory stability in changing environments. The Proportional-Integral-Derivative (PID) control is less responsive because the parameters are set manually. Previous studies have attempted to combine Fuzzy-PID with Extended Kalman Filter (EKF). Previous approaches improved control but remained sensitive to disturbances. This study proposes an EKF-based Fuzzy-PID control where the PID parameters are adjusted automatically using Fuzzy and EKF functions to adjust the Fuzzy parameters adaptively. The proposed control method minimizes angular and linear errors under various conditions. From the simulation, the system is able to follow the reference with high precision, with position errors of x, y, z axis are 0.15 m, 0.12 m, and 0.10
m respectively. The low z-axis error indicates stable altitude control. Under disturbances, the average position error increases by only about 0.09 m on each axis. It shows that the EKF-based Fuzzy-PID controller has effective and adaptive performance in uncertain environments.