NMPC based path following for a small fixed-wing unmanned aerial vehicle in a dynamic environment

The goal of the paper is to make a fixed-wing unmanned aerial vehicle (UAV) follow a predefined path while avoiding previously unknown obstacles including pop-up threats and the moving obstacle in a dynamic environment. The predefined path is represented by a Pythagorean Hodograph (PH) curve and the nonlinear model predictive control (NMPC) algorithm is used for real-time PH path following and collision avoidance in view of pop-up threats and the moving obstacle. A new form of cost function for the NMPC is proposed, which includes a navigation cost function for the PH path following a new type of collision avoidance cost for large obstacle avoidance, and an additional function penalizing the cost function in the case of the UAV flying back after obstacle avoidance. MATLAB based simulation experiments are performed to demonstrate the effectiveness of the algorithm. It is shown that the proposed algorithm is able to successfully avoid unknown obstacles in a dynamic environment while following the predefined PH path.