Enhancing Quadrotor UAV Efficiency Amidst Turbulent Winds in Mangrove Area: A Hybrid PID-Grey Wolf Optimizer Control Approach

Quadrotor Unmanned Aerial Vehicles (UAVs) offer versatile platforms for various applications including disaster response and environmental monitoring. However, their effective utilization in wind-disturbed environments such as mangroves poses unique challenges due to complex wind turbulence, impacting flight stability and navigation accuracy. Traditional control systems often fall short of ensuring robust and precise control in such conditions. This study presents a hybrid control approach combining a Proportional-Integral-Derivative (PID) control system with the Grey Wolf Optimizer (GWO) for enhanced UAV performance in challenging conditions. The PID controller, known for its effectiveness in industrial control systems, provides a control loop feedback mechanism to minimize flight errors, while the GWO, a bio-inspired optimization algorithm, automates the process of tuning PID parameters. Preliminary results show that this hybrid PID-GWO system significantly improves the UAV's robustness and adaptability under varying wind conditions, outperforming the standalone PID controller. This research illuminates a new direction for optimizing UAV performance in wind-disturbed environments and suggests further exploration of bio-inspired optimization techniques in UAV control systems.