Optimal PID φ axis Control for UAV Quadrotor based on Multi-Objective PSO

In this paper, we tackle the problem of PID Control tuning for a quadrotor. This task is vital given the several applications a UAV quadrotor can perform. This paper focuses on the optimal PID controller tuning in phi axes. We propose using a Multi-objective Particle Swarm Optimization (PSO) algorithm for PID performance improvement. The proposed system is evaluated in a Parrot Mambo FPV UAV Quadrotor virtual model using MATLAB & Simulink environment. We compare four different cost functions for the multi-objective optimization approach. Those cost functions focus on improving the UAV performance based on the settling time, overshoot, steady-state error, and control effort. The evaluation system shows the best performance in combining the different factors through the Multi-objective PSO algorithm. Copyright (C) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)