This review article provides a comprehensive analysis of the control systems for Unmanned Aerial Vehicles (UAVs), focusing on current trends and future directions. The primary objective is to synthesize recent advancements, evaluate emerging technologies, and identify future research pathways in UAV control systems. The review article includes various UAV types, control system types and architectures, some key technologies, and also the actuators and sensor faults in UAVs. Key findings include advancements in autonomous navigation, Swarm UAVs, and the integration of artificial intelligence and machine learning (AI and ML) techniques. Hybrid control systems are another emerging mechanism that integrates different control strategies to optimize performance. Advancements in sensor technology, communication systems, and AI are driving the evolution of UAV control systems. The applications of UAVs presented in this article demonstrate the versatility and growing importance of UAVs across various sectors. Furthermore, some challenges and limitations of control algorithms are also presented. Future directions include advanced hybrid models, enhanced AI integration, hardware in the loop (HIL) simulations, brain-computer interface (BCI) remote control, and emerging optical communication technologies are also discussed. Sustainable UAV operations and evolving regulatory frameworks will play critical roles in shaping the future landscape of UAV control systems.
Abdullah et al. (2026) studied this question.