PARTICLE SWARM OPTIMIZATION BASED OPTIMAL PID CONTROLLER FOR QUADCOPTERS

A novel particle swarm optimization (PSO) based optimal PID controller for quad-copters is proposed in this paper. A mathematical model of the quadcopter is derived first. A PID controller for attitude control is proposed. Parameters of the PID controller are found using PSO algorithm. Two stages of optimization are conducted. The novelty of this study is that the two stages are conducted differently; in the first stage no disturbance is used while in the second stage several different disturbance magnitudes are used to fine tune the controller. In the first stage, coarse parameters are found with zero disturbance experiments. These parameters are fed as initial parameters for a second stage of optimization. In the second stage, parameters are fine-tuned under various magnitudes of disturbance. Disturbance is used to simulate wind, noise and other unpredictable effects. Results are given as figures and summarized as a table. Simulation results show that the second stage of optimization clearly enhances performance of disturbance rejection.