A continuous modeling method via improved pigeon-inspired optimization for wake vortices in UAVs close formation flight

This paper explores the modeling of wake vortices to estimate the wake vortex effect in unmanned aerial vehicles (UAVs) close formation flight. A continuous horseshoe vortex method is proposed based on the consideration of a compromise between estimation accuracy and computational efficiency. Using the proposed modeling method, the wake vortex model can easily adapt to UAVs with different wing shapes by adjusting model parameters. Furthermore, the interaction coefficient of filaments of the wake vortex is introduced to improve the estimation accuracy. However, the analytical value is solved difficultly by theoretical derivation. Therefore, the improved pigeon-inspired optimization is developed to search for the optimal value. On the other hand, the wake vortex effect is formulated by the statistical average strategy. The formulated wake vortex effect can be readily utilized to conduct a realistic dynamic model of the vortex-suffering UAV. Simulation results show that the estimation accuracy of the proposed modeling method increases by approximately 30% and 34%, compared with the single and multiple horseshoe vortex methods respectively. Furthermore, the computational efficiency is sufficient enough for the real-time estimation in UAVs close formation flight.