ANALYSIS OF CONTROL ARCHITECTURES FOR UNMANNED AERIAL VEHICLES

Abstract

Unmanned aerial vehicles (UAVs) have become important components of modern systems for monitoring, inspection, mapping, and autonomous intervention. Their performance directly depends on the efficiency of the control systems and the architecture used for data processing, decision-making, and mission coordination. The paper presents a comparative analysis of the main control architectures used in UAV platforms: control with on-board processing (On-Board Control), hierarchical Master-Swarm architecture, and centralized systems based on a Ground Control System (GCS). It describes the operating principles of each architecture, the hardware and software components involved, advantages, limitations, and specific areas of application. The analysis highlights the impact of each solution on autonomy, scalability, resilience to communication loss, and real-time control performance. The results obtained show that On-Board Control systems offer superior autonomy and robustness, Master-Swarm architectures are intended particularly for the collaborative coordination of drone swarms, and GCS systems provide advanced capabilities for monitoring and centralized processing. Furthermore, current trends oriented towards hybrid architectures are highlighted, which combine the advantages of the three models to increase the level of autonomy, safety, and operational efficiency of modern UAV systems.