Comprehensive Optimization of Energy Storage and Standoff Tracking for Solar-Powered UAV

Compared with traditional unmanned aerial vehicle (UAV), the solar-powered UAV (SUAV) has longer endurance by converting solar energy into electric energy. This article focuses on the comprehensive optimization of energy storage and standoff tracking performance for SUAV with application to the target tracking task. First, an adjustable Lyapunov guidance vector field (ALGVF) is proposed and combined with the interfered fluid dynamical system (IFDS) method to achieve the standoff target tracking mission in obstacle environment, making it possible to adjust the tracking trajectory flexibly. Then, the adjustment factor of ALGVF and the obstacle reaction coefficients of IFDS are optimized simultaneously to generate the optimal trajectory of SUAV, aiming to maximize the solar energy storage while minimize the tracking error. Finally, the simulation results verify the feasibility of our method and give the influence of different solar irradiance on SUAV trajectory optimization.