Real-Time Second-Order Optimal Guidance Strategies for Optimizing Aircraft Performance in Stochastic Wind Conditions
Kamran Turkoglu

TL;DR
This paper introduces real-time guidance strategies for UAVs that leverage in-situ wind measurements to optimize flight paths, significantly improving endurance by reducing power consumption through second-order optimal control methods.
Contribution
The study develops a novel real-time guidance approach using second-order optimal control and stochastic wind modeling to enhance UAV endurance in variable wind conditions.
Findings
Potential power savings demonstrated through simulations.
Strategies effectively utilize wind energy for endurance improvement.
Performance improvements quantified over various scenarios.
Abstract
This study presents a real-time guidance strategy for an unmanned aerial vehicles (UAVs) that can be used to enhance their flight endurance by utilizing {\sl insitu} measurements of wind speeds and wind gradients. In these strategies, periodic adjustments are made in the airspeed and/or heading angle command, in level flights, for the UAV to minimize a projected power requirement. In this study, UAV dynamics are described by a three-dimensional dynamic point-mass model. A stochastic wind field model has been used to analyze the effect of the wind in the process. 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…
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Taxonomy
TopicsAerospace and Aviation Technology · Guidance and Control Systems · Aerospace Engineering and Control Systems
