Optimisation of nonlinear controllers for a quadrotor using metaheuristic algorithm

Abstract

Unmanned aerial vehicles (UAVs) facilitate complex activities and are widely used for aerial transport. Quadrotor UAVs (QUAV), the most popular UAV containing four motors, are characterised by higher control properties since they have fewer actuators than degrees of freedom, implying a nonlinear underactuated system. In addition, the coupling of dynamics, flaws while modelling and parameter uncertainty are the factors that hinder the design and implementation of a controller. Here, we present the modelling, optimisation, simulation, and implementation methodology for controllers, proportional-integral-derivative (PID), and super-twisting-sliding mode control (ST-SMC). We carry out the parameterisation problem of controllers using the hunger game search (HGS) metaheuristic algorithm. This process was developed offline, and the values obtained were successfully implemented in simulation and experimental form. The testing platform comprises a motion capture system, Vicon® Bonita cameras, linked by ROS, that allows the known position and the attitude of a Parrot® QUAV bebop1. The whole six dynamics of the QUAV are included in the implementation, translational trajectories X-Y are trapezoidal, and the altitude trajectory is a ramp. The results enabled the comparison of the statistics calculation of each controller. Successful tracking trajectories were obtained even with disturbance when the ST-SMC algorithm was implemented with root mean square error (RMSE)=0.0176.