Energy-optimal path planning for Solar-powered UAV with tracking moving ground target

This paper presents the novel use of receding horizon control (RHC) with particle swarm optimization (PSO) to generate the energy-optimal trajectories for Solar-powered Unmanned Air Vehicle (SUAV) with the mission of target tracking. Firstly, an integrated model is presented that accounts for the couplings, such as kinematics, energetics and mission. The model can formulate the relationship between the aircraft's position or attitude and the solar time or angle at anytime and anywhere in the world. Next, the mission of tracking moving ground target is studied in this paper, which is unique relative to past work about the SUAV. At the same time, to collect more energy and track the moving ground target, the optimization method of RHC with PSO is used here. To evaluate optimization performance, some performance indexes are put forward, and the definitions of them are given. Finally, several numerical simulations demonstrate that this method is feasible and flexible to generate the energy-optimal route for solar-powered UAV online with tracking ground moving target. The analysis of simulations results indicates that it's possible to carry out the task of tracking maneuvering target for a longer time for SUAV.