Robust Trajectory Tracking Control and Obstacles Avoidance Algorithm for Quadrotor Unmanned Aerial Vehicle

This paper addresses the designing of a robust controller for an automatic landing, trajectory tracking and take-off missions of quadrotor unmanned aerial vehicle (QUAV). This has been investigated where the QUAV's dynamic model involves nonlinearity, uncertainties, and coupling which makes the QUAV has a very complex system. The proposed controller can control both the position and orientation in addition to control the driving motors. For controlling the position, an appropriate control signal is generated for adjusting the altitude of the QUAV in a working space. To achieve this, three adaptive fuzzy controllers have been designed for three-dimensional coordinates i.e. x, y and z axes. For orientation control, three proportional derivative integral controllers (PIDCs) are introduced to control pitch, roll and yaw angles and make them reaching the desired values. Moreover, PID controllers are proposed for controlling the four driving motors. The parameters of both fuzzy and PID controllers are tuned by using particle swarm optimization (PSO) algorithm which enables the selection of the optimal values for each controller. For comparison purposes, the adaptive fuzzy controllers in the first layer of the proposed control system are replaced with PIDCs to prove the effectiveness of the proposed control system. Furthermore, a Lyaounov theory is utilized for studying the stability of fuzzy controllers. The proposed control system is capable of guiding the QUAV to track the previously defined reference trajectories. For obstacle avoidance, a vector field histogram algorithm is used to avoid collision of the QUAV with obstructing obstacles that block the QUAV's path.