HALE, UAV, Drone, Trajectory, MPC, Optimization, Solar
This paper demonstrates the use of nonlinear dynamic optimization to calculate energy optimal trajectories for a high-altitude, solar-powered Unmanned Aerial Vehicle (UAV). The objective is to maximize the total energy in the system while staying within a 3 km mission radius and meeting other system constraints. Solar energy capture is modeled using the vehicle orientation and solar position, and energy is stored both in batteries and in potential energy through elevation gain. Energy capture is maximized by optimally adjusting the angle of the aircraft surface relative to the sun. The UAV flight and energy system dynamics are optimized over a 24-hour period at an eight-second time resolution using Nonlinear Model Predictive Control (NMPC). Results of the simulated flights are presented for all four seasons, showing 8.2% increase in end-of-day battery energy for the most limiting flight condition of the winter solstice.
BYU ScholarsArchive Citation
Martin, Abe; Gates, Nathaniel S.; Ning, Andrew; and Hedengren, John, "Dynamic Optimization of High-Altitude Solar Aircraft Trajectories Under Station-Keeping Constraints" (2018). All Student Publications. 243.
Ira A. Fulton College of Engineering and Technology
Copyright © 2018 by R. Abraham Martin, Nathaniel S. Gates, Andrew Ning, and John D. Hedengren. This is the author's submitted version of this article. The definitive version is published by the American Institute of Aeronautics and Astronautics, Inc., with permission, and can be found at https://doi.org/10.2514/1.G003737.
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