Automated Landing of an Unmanned Aerial Vehicleon a Mobile Platform Using Neural Networks

The development of unmanned aerial vehicles is one of the promising directions for civil aviation with a wide range of applications. Neural networks can be trained for real-time decision making, adapting to changing battlefield conditions and ensuring optimal task execution. Among many UAV navigation and control tasks, the challenge of automatic landing of an unmanned aerial vehicle on a mobile landing platform (ships, vehicles, specialized platforms) remains relevant. Automated landing of an unmanned aerial vehicle on a mobile carrier is particularly significant.The article examines the system of automatic landing of an unmanned aerial vehicle (UAV) on a mobile platform using neural network technologies. The research method is based on the application of artificial neural networks for developing an adaptive control system capable of real-time decision-making during landing maneuvers.As a result of the research, a control algorithm was developed that ensures precise landing of UAVs on various types of moving platforms (ships, vehicles, specialized platforms), which significantly expands the operational range of unmanned vehicles and increases their efficiency in various operating conditions.