AR.DRONE 2.0 QUADROTOR PATH CONTROL VIA LQR AND Hinfinity APPROACHES
LQR, H1 control, optimal control, quadcopter, model identification, LMI
This work presents an experimental study of two control techniques based on the Optimal Control theory, applied to an unmanned aerial vehicle (UAV). The first technique, based on the quadratic cost function, is the LQR controller. The second technique optimizes the norm Hinfinity taking into account the pole allocation and using an approach based on LMIs. The mathematical modeling of the vehicle is presented, along with experiments to carry out the identification and validation of the model's parameters. Furthermore, practical tests are carried out in order to investigate the performance of each controller, with and without the presence of external disturbances. The test platform used is the quadrotor AR.Drone 2.0 and the algorithms are implemented in the Robot Operating
System (ROS).