Design Concept of Angular Controller for Quadrotor UAV Based on Improved Particle Swarm Optimization Algorithm PID Control

The control of unmanned aerial vehicles (UAVs) is a key research problem in the field of UAVs. PID control is currently one of the most widely used methods for this issue. However, the classical PID control structure suffers from difficulty tuning control parameters, resulting in poor control performance for UAVs. Therefore, this paper proposes a Gaussian mutation-enhanced PSO-PID algorithm for UAV control. The proposed method is built upon classical PID control and PSO optimization algorithms. Firstly, the dynamic model of UAV is constructed using Euler's method and Newton's laws of motion. Then, single-loop PID control is applied to control the UAV, and the PSO algorithm is introduced to solve the parameter tuning problem. To overcome the drawback of PSO algorithm being prone to local optima, Gaussian mutation is introduced to enhance the ability to escape from local optima. The algorithm theoretically offers faster response and better control performance compared to the classical PID structure, and it can be used as a flight control algorithm for commercial UAVs in the future.