Design of fuzzy PID control system for quad-rotor UAV based on particle swarm algorithm under wind disturbance conditions

This project proposes an intelligent control method that employs a particle swarm algorithm to optimize the rules of a fuzzy controller. The rules of the fuzzy controller are continuously adjusted based on feedback data on the attitude changes of a quadrotor unmanned aerial vehicle and the enhanced particle swarm algorithm. This enables the controller to learn autonomously, thereby enhancing its performance under various conditions. In addition to optimizing the rules of the fuzzy controller, an analysis and modeling process is conducted for the characteristics of wind speed changes under natural conditions. The resulting model is introduced into the system as environmental noise, thereby improving the controller’s performance under different conditions. Experiments are conducted in the Matlab/Simulink simulation environment to test the performance of the control algorithm. The algorithm’s anti-disturbance capability and control accuracy are compared when facing complex disturbances. This research methodology offers new possibilities for precise control of quadrotor unmanned aerial vehicles and provides valuable references for future drone technology development.