https://orcid.org/0009-0005-0930-1576
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.
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