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Real-time Guidance Strategies for Optimizing Aircraft Performance in Stochastic Wind Conditions
American Control Conference (ACC) (2014)
  • Kamran Turkoglu, San Jose State University

This study presents real-time guidance strategies for unmanned aerial vehicles (UAVs) that can be used to enhance their flight endurance by utilizing insitu measurements of wind speeds and wind gradients. In these strategies, periodic adjustments can be made in the airspeed and/or heading angle command for the UAV to minimize a projected power requirement at some future time. In this research, UAV flights are described by a three-dimensional dynamic point-mass model. Onboard closed-loop trajectory tracking logics that follow airspeed vector commands are modeled using the method of feedback linearization. To evaluate the benefits of these strategies in enhancing UAV flight endurance, a reference strategy is introduced in which the UAV would follow the optimal airspeed command in a steady level flight under zero wind conditions. A performance measure is defined as the average power consumption both over a specified time interval and over different initial heading angles of the UAV. A relative benefit criterion is then defined as the percentage improvement in the performance measure of a proposed strategy over that of the reference strategy. Extensive numerical simulations are conducted to show efficiency and applicability of the proposed algorithms. Results demonstrate the efficiency, benefits and trends of power savings of the proposed real-time guidance strategies in level flights.

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Kamran Turkoglu. "Real-time Guidance Strategies for Optimizing Aircraft Performance in Stochastic Wind Conditions" American Control Conference (ACC) (2014)
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