Particle Swarm Optimization Applied to Hexarotor Flight Dynamics

Abstract

In this work, results obtained by the flight control simulations of a prototype of hexarotor Unmanned Aerial Vehicle (UAV) are shown. The mathematical model and control of the hexacopter airframe are presented. To stabilize the entire system, Linear Quadratic Regulator (LQR) control is used in such a way to set both Proportional Derivative (PD) and Proportional Integral Derivative (PID) controls. Particle Swarm Optimization has been used to set the optimal coefficient matrices of the LQR control algorithm. The simulations are performed to show how LQR tuned PD and PID controllers lead to zero the error of the position along gravity acceleration direction, stop the rotation of UAV around body axes and stabilize the hexarotor. Moreover, the obtained LQR-PD and LQR-PID controllers have been tested by comparing the response to impulse disturbances of the nonlinear dynamical system with the response of the linearized one.