High altitude-long endurance, aircraft optimization, combined design and control, station keeping, trajectory, energy minimization, UAV
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.
Original Publication Citation
BYU ScholarsArchive Citation
Martin, Ronald Abraham; Gates, Nathaniel; Ning, Andrew; and Hedengren, John, "Dynamic Optimization of High-Altitude Solar Aircraft Trajectories Under Station-Keeping Constraints" (2018). Faculty Publications. 4055.
Ira A. Fulton College of Engineering and Technology
Copyright © 2018 by R. Abraham Martin, Nathaniel S. Gates, Andrew Ning, and John D. Hedengren. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the ISSN 0731-5090 (print) or 1533-3884 (online) to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp.
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