An Improved Artificial Potential Field Method for Dynamic Obstacle Avoidance Control of Unmanned Aerial Vehicle with Motor Fault

An improved obstacle avoidance control strategy for quadrotor unmanned aerial vehicles (UAVs) to handle both motor loss-of-effectiveness fault and dynamic obstacles is proposed in this paper. The strategy is based on an improved artificial potential field method, which incorporates a repulsion field based on both relative position and velocity factors to address the limitations of traditional repulsion fields when navigating dynamic obstacles. The proposed obstacle avoidance strategy demonstrates effective maneuvering around dynamic obstacles. Within the tracking loop, a fault-tolerant controller is designed by employing Backstepping technology, featuring fault estimation capabilities. The adaptive mechanism is employed for online estimation of unknown fault factors and upper bounds of external disturbances. The stability of the closed-loop system is rigorously proven by Lyapunov stability theory. Ultimately, simulation results provide empirical evidence of the effectiveness of the proposed control algorithm.