Fuzzy Logic-Based Dynamic Prioritization for UAV Wireless Charging Systems in Agriculture

This research work presents an advanced Unmanned Aerial Vehicle (UAV) wireless charging system with notable improvements in sustainability and adaptability. The system utilizes an adaptive fuzzy logic controller that offers adjustable charging priority in real time with respect to State of Charge, Arrival Time, and Energy Demand. Designed to execute best in agricultural and industrial environments, the system gives its users efficient UAV charging by considering environmental information in real-time. So, starting from agriculture, it is now possible for UAVs to fly for long periods over critical tasks of crop observation, while in industrial settings, the system enables fast recharging for inspection operations. The MATLAB Simulink model was improved such as to give detailed simulations, which have clearly illustrated how the system reacts to different working conditions as well as self-adjusts its charging schedule. One of the proposals offered in order to extend the period of flight even more is the use of a dual-UAV system. This will enable role-switching during low battery levels, thus maintaining unobstructed operations while the other UAV gets charged.