Organizational Unit:
Aerospace Design Group

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Now showing 1 - 2 of 2
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    Flight-Test Results of Autonomous Airplane Transitions Between Steady-Level and Hovering Flight
    (Georgia Institute of Technology, 2008-03) Johnson, Eric N. ; Wu, Allen D. ; Neidhoefer, James C. ; Kannan, Suresh K. ; Turbe, Michael A.
    Linear systems can be used to adequately model and control an aircraft in either ideal steady-level flight or in ideal hovering flight. However, constructing a single unified system capable of adequately modeling or controlling an airplane in steady-level flight and in hovering flight, as well as during the highly nonlinear transitions between the two, requires the use of more complex systems, such as scheduled-linear, nonlinear, or stable adaptive systems. This paper discusses the use of dynamic inversion with real-time neural network adaptation as a means to provide a single adaptive controller capable of controlling a fixed-wing unmanned aircraft system in all three flight phases: steady-level flight, hovering flight, and the transitions between them. Having a single controller that can achieve and transition between steady-level and hovering flight allows utilization of the entire low-speed flight envelope, even beyond stall conditions. This method is applied to the GTEdge, an eight-foot wingspan, fixed-wing unmanned aircraft system that has been fully instrumented for autonomous flight. This paper presents data from actual flight-test experiments in which the airplane transitions from high-speed, steady-level flight into a hovering condition and then back again.
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    Flight Results of Autonomous Fixed-Wing UAV Transitions to and from Stationary Hover
    (Georgia Institute of Technology, 2006-08) Johnson, Eric N. ; Turbe, Michael A. ; Wu, Allen D. ; Kannan, Suresh K. ; Neidhoefer, James C.
    Fixed-wing unmanned aerial vehicles (UAVs) with the ability to hover have significant potential for applications in urban or other constrained environments where the combination of fast speed, endurance, and stable hovering flight can provide strategic advantages. This paper discusses the use of dynamic inversion with neural network adaptation to provide an adaptive controller capable of transitioning a fixed-wing UAV to and from hovering flight in a nearly stationary position. This approach allows utilization of the entire low speed flight envelope even beyond stall conditions. The method is applied to the GTEdge, an 8.75 foot wing span fixed-wing aerobatic UAV which has been fully instrumented for autonomous flight. Results from actual flight test experiments of the system where the airplane transitions from high speed steady flight into a stationary hover and then back are presented.