Evaluation of Fractional Proportional-Integral-Derivative and Integer Proportional-Integral-Derivative Control for a Drone-Based Cable Suspended Payload System

Abstract

Abstract Arctic remote sensing is crucial for studying and preserving the vulnerable Arctic environment. Researchers use ground penetrating radars (GPRs) to understand climate change and ice properties, but maneuvering a bulky GPR on the inhospitable Arctic terrain is difficult. Suspending the GPR from a drone can be a solution to operating a large GPR, however, proper control and stabilization of the drone-GPR system pose a challenge. In this paper, we contribute to the literature by analyzing the response of closed-loop feedback fractional-order and integer-order proportional-integral-derivative (PID) controllers at minimizing the payload sway for a drone-based cable-suspended payload system. Both controllers were tuned using particle swarm optimization and simulated to experience delays and external disturbances. Results indicate that both controllers had comparable time responses. The fractional-order controller was more robust to disturbances but was also sensitive to system delays. The findings of this study can be considered for future drone development.