Simulation and Optimization of UAV Group Control Strategies

In recent years, extensive research has been conducted to develop methods and algorithms for controlling the coordinated motion and interaction of autonomous unmanned aerial vehicles (UAVs). The issue of UAV control in real-world conditions, especially when controlling autonomous unmanned vehicles like airplanes, remains relevant. The complexity of such control is due to the high dynamics and input constraints of real-world autopilots. This paper presents an adaptive control strategy for unmanned aerial vehicle (UAV) group coordination, integrating integral control laws and fuzzy logic to improve dynamic formation stability and energy efficiency. A simulation environment was developed in MATLAB/Simulink to evaluate the proposed strategy. Simulation experiments demonstrated superior responsiveness, reduced trajectory deviation, and increased robustness against external disturbances compared to traditional methods. The results validate the viability of the proposed control scheme in real-time multi-agent UAV systems operating under dynamic and uncertain conditions.