Abstract
Transition towers and conveyor structures in steel industries, which are utilized for material transfer, require regular visual inspections to ensure optimal performance. However, due to their high altitude and challenging environmental conditions—such as strong winds and extreme dust—these inspections are both costly and labor-intensive for decision-makers. Additionally, severe dust necessitates frequent maintenance of any wireless cameras installed for continuous monitoring, as they require regular cleaning and cannot cover all sections of the area. Tiltrotor quadcopters have emerged as a promising solution for inspecting these industrial structures at hard-to-reach locations within large-scale environments. Nevertheless, wind disturbances, particularly at high altitudes, pose a significant challenge. Therefore, implementing a robust control system capable of maintaining stable performance under such conditions is essential. In this paper, we introduce a tiltrotor quadcopter control system based on a gain-scheduled controller (GSC). Our choice of this control method is motivated by its potential to effectively manage wind disturbances during structural inspections and to capture images of the specified structures. We provide a mathematical formulation of the GSC method and present performance simulations using MATLAB and a machine learning approach. We evaluated and monitored the control method's performance, observing satisfactory chattering levels relative to those reported in the literature for the specified environment. The proposed GSC-based control system demonstrates potential for stabilizing tiltrotor quadcopter flight under wind disturbances in industrial inspection scenarios. Future work will focus on experimental validation and extension to full 6-DOF coupled dynamics.