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

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 level flight under zero wind conditions. A performance measure is defined as the average power consumption with respect to no wind case. Different scenarios have been evaluated 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 possible power savings of the proposed real-time guidance strategies in level flights, by utilization of wind energy.