ANALYSIS OF UAV CONTROL METHODS (GPS POSITIONING AND INTELLIGENT CONTROL METHODS) - TANASIYCHUK, STEPAN; HOVORUSHCHENKO, TETIANA (Herald of Khmelnytskyi National University. Technical sciences, 2024)
An analysis of UAV control methods was conducted, noting that during the construction of UAV control systems, the command element or its part is moved beyond the aircraft and connected to the executive element via a transmission line. The main function solved by the control system (CS) is controlling the movement of the center of mass (three control channels) and the angular movements of the UAV relative to the center of mass (three control channels). Thus, UAV flight control is reduced to controlling its motion parameters: angular coordinates, angular velocities and accelerations, linear coordinates (distance, altitude, lateral displacement). For UAVs with high-speed characteristics and high maneuverability, very fast delivery of control commands from the control point to the onboard system is required. Concurrently, manual control requires a high degree of operator intervention in the aircraft control process, which, in turn, demands high operator concentration and a high level of training.It is emphasized that intelligent control methods for UAVs are an important component of modern unmanned systems. They allow for piloting and controlling drones with high precision and efficiency, automatically performing various tasks. In this context, UAVs can be used for gathering information from altitude, which increases the area that can be covered at once. Thus, UAVs can be used for detecting fires over large areas, such as forested areas, where timely fire detection is critically important. The basic principles of GPS system operation and its role in UAV navigation are described. Special attention was given to intelligent flight modes of UAVs. These include automatic piloting, precise positioning, obstacle detection, and other functions that enable drones to autonomously perform tasks with high precision.
Keywords: Drone; SLAM; GPS; positioning; neural network; robust control; Composition Mode; position shift