Adaptive algorithms for drone flight control under communication constraints and information incompleteness

Abstract With the rapid increase in the use of drones in various applications, including commercial and governmental, and the increasing probability of communication failures and contingencies, research becomes critical to ensure the safety and efficiency of their operations. The aim of this research is to develop adaptive drone flight control algorithms capable of operating effectively under conditions of limited communication and incomplete information to ensure reliable and safe autonomous operation of these systems. The applied methods include computer modelling and simulation, analytical, statistical, functional, deductive and descriptive methods. The study found that the use of performance evaluation methods for complex systems enables the identification of safety and performance criteria for drones, and drone flight control provides basic principles and methods that can be adapted for drones, including autopiloting and navigation. In addition, analyses of satellite communication and navigation prove the need to consider the limitations of this technology when developing drone control algorithms. The combination of these techniques allows for more robust and adaptive drone control systems that can function effectively in complex environments such as communication limitations and incomplete information. Additionally, it was found that the integration of adaptive control algorithms based on these methods allows drones to effectively adapt to variable environmental conditions and make decisions quickly even when communication is lost or information is limited.