PID parameter tuning algorithm of rotor UAV Based on Improved Particle Swarm Optimization

Abstract

Aiming at the shortcomings of cascade proportional integral derivative (PID) in the flight control system of small rotary-wing UAV flight control system, it is difficult to manually adjust the parameters and the parameters obtained after the optimization is poor, an improved particle swarm algorithm with nonlinear dynamic weights is proposed., And use it in the tuning process of UAV PID parameters. Taking the quad-rotor UAV as the specific research object, firstly, the mathematical model of the UAV is established, and an improved particle swarm optimization method is adopted to process the inertial weights for nonlinear dynamic drop processing, which greatly improves its search performance and optimization efficiency. To make up for the shortcomings of the traditional particle swarm optimization method, finally through Matlab/Simulink simulation comparison and analysis. The experimental results show that the parameters adjusted by the improved particle swarm optimization method can enable the system to achieve better control performance indicators and shorter adjustment time, so that the UAV has a better dynamic performance, and it also eliminates manual tuning. It reduces the time of parameter setting and has certain guiding significance for practical engineering applications.