Particle Swarm Optimized Robust Backstepping Control of a Quadrotor Unmanned Aerial Vehicle under Pink Noise

Abstract

Technological developments in sensors, actuators, and energy storage devices have allowed the development of quadrotor unmanned aerial vehicles (UAVs). Quadrotor UAVs are used in sensitive tasks such as surveillance, search and rescue, mapping, mining, cargo carriage, agricultural spraying, firefighting, and photography. Quadrotor UAVs are exposed to effects such as noise and vibration while performing these sensitive tasks. Therefore, robust controller design that is resistant to noise and vibration gains great importance. Noise and vibration can be caused by the sensors, actuator, and propellers of the quadrotor. Background noise in electronic devices is called pink noise. The primary sources of pink noise in electronic devices are generally slow fluctuations of the properties of the condensed matter materials of the devices. These contain fluctuating defect configurations in metals, fluctuating trap occupancy in semiconductors, and fluctuating field structures in magnetic materials. In this study, a particle swarm optimized (PSO) robust backstepping controller is designed for a quadrotor that can follow altitude and attitude references under pink noise. The rise time, overshoot, and settling time of the PSO-optimized proposed backstepping controller and classical PID controller were compared. It has been proven by simulations that the designed PSO-optimized backstepping controller performs more successfully than the classical PID controller.