TY - JOUR
T1 - Flight-test results of autonomous airplane transitions between steady-level and hovering flight
AU - Johnson, Eric N.
AU - Wu, Allen
AU - Neidhoefer, James C.
AU - Kannan, Suresh K.
AU - Turbe, Michael A.
N1 - Funding Information:
This work was supported in part by AeroVironment, Inc., Guided Systems Technologies, and the Active-Vision Control Systems Multi-University Research Initiative Program under contract #F49620-03-1-0401. The authors would like to thank the following people for their contributions to the work presented in this paper: Michael Cancienne, J. Eric Corban, Claus Christmann, Henrik Christophersen, Jason Fine, Stewart Geyer, Jeong Hur, Wayne Pickell, Nimrod Rooz, and Brent Yates.
PY - 2008
Y1 - 2008
N2 - Linear systems can beusedto adequately model and controlanaircraft 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 flighttest experiments in which the airplane transitions from high-speed, steady-level flight into a hovering condition and then back again.
AB - Linear systems can beusedto adequately model and controlanaircraft 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 flighttest experiments in which the airplane transitions from high-speed, steady-level flight into a hovering condition and then back again.
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U2 - 10.2514/1.29261
DO - 10.2514/1.29261
M3 - Article
AN - SCOPUS:44649105720
SN - 0731-5090
VL - 31
SP - 358
EP - 370
JO - Journal of Guidance, Control, and Dynamics
JF - Journal of Guidance, Control, and Dynamics
IS - 2
ER -