@article{TAN2026, 
author = {Liguo TAN and Yongcheng XIONG and Changqing HU and Jianfeng LI and Oleg KUZENKOV and Samvel NALCHAJYAN},
title = {Parametric control of UAV U-turns in turbulent wind conditions based on global optimization},
year = {2026},
journal = {Chinese Journal of Aeronautics},
volume = {39},
number = {1},
keywords = {Parametric control, Rigid-wing unmanned aerial vehicle, Stochastic system, Global optimization, Evolutionary algorithm},
url = {https://www.sciopen.com/article/10.1016/j.cja.2025.103746},
doi = {10.1016/j.cja.2025.103746},
abstract = {Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning, which can significantly compromise control and reduce autopilot effectiveness. This paper presents a novel control strategy to improve the controllability of unmanned aircraft in challenging wind conditions. First, the equations of motion for the aircraft are reformulated as a system of stochastic differential equations, which are subsequently transformed into a deterministic form. By modeling turbulence as a Gaussian random process and incorporating it directly into the control system, the proposed method proactively compensates for the adverse effects of turbulence. The transformation is achieved using semi-invariant techniques. Second, the control problem is formulated as an optimization task, aiming to minimize the deviation between the actual and desired turn characteristics, specifically the angular velocity. Finally, a new numerical method with proven global convergence is employed to compute the optimal autopilot parameters. Simulation results using a medium-range unmanned aircraft model under continuous turbulent gusts demonstrate that the proposed method significantly outperforms existing approaches, ensuring both stability and precision in turbulent wind conditions.}
}