A Comprehensive Study on Design and Control of Unmanned Aerial Vehicles

The growing use of Unmanned Aerial Vehicles (UAVs) in fields such as environmental monitoring, agriculture, and defense has led to significant advancements in UAV design and control. This paper explores the hardware and software components of UAV control systems, focusing on material selection, aerodynamics, power systems, and control strategies that incorporate sensor integration, autonomous navigation, and machine learning algorithms. The research investigates the effectiveness of AI-driven models and real-time feedback systems, highlighting the improvements in UAV maneuverability, efficiency, and autonomy. Despite challenges such as limited flight time and energy consumption, the study calls for more resilient UAV architectures capable of operating in extreme conditions. The findings suggest that continued research into UAV autonomy, endurance, and environmental adaptability is crucial for meeting the growing demands of industries requiring long-duration flights and high levels of autonomy.