Approaches to real-time adaptive prediction of loss-of- control margins with visual cue feedback
Rafi, Melvin Steck, James E. Chakravarthy, Animesh
Rafi, Melvin
Steck, James E.
Chakravarthy, Animesh
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Authors
Rafi, Melvin
Steck, James E.
Chakravarthy, Animesh
Steck, James E.
Chakravarthy, Animesh
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Issue Date
2018-01-08
Type
Conference paper
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Keywords
Ailerons,Copilot,Aircraft dynamics,Elevator deflection,Aerodynamics,Angle of sideslip,Linear Quadratic Regulator,Flight envelope,Flight testing,Numerical integration
Subjects (LCSH)
Citation
Rafi, M., Steck, J. E., & Chakravarthy, A. (2018). Approaches to real-time adaptive prediction of loss-of- control margins with visual cue feedback. Paper presented at the AIAA Guidance, Navigation, and Control Conference, 2018, (210039) doi:10.2514/6.2018-1123 Retrieved from www.scopus.com
Abstract
Loss-of-Control events continue to be the most significant contributing factor to air accidents worldwide. Predictive systems capable of warning pilots of impending entry into a control loss event have the potential to promote safer flight. Towards this goal, two prediction models are developed which adaptively calculate an aircraft's proximity to its loss-of-control margins given current-time pilot inputs. The first model utilizes analytical expressions for the time domain response of the 1st and 2nd order aircraft modes to predict critical control deflections, while the second model utilizes a linear quadratic tracker to predict critical control trajectories. Adaptive parameter estimation is implemented to facilitate real-time modeling error identification, to account for non-linearities, failures, or uncertainties in the
aircraft model. Two head-up advisory displays are developed to present the predicted control limits and loss-of-control margins to the pilot, providing pre-emptive warning if impending
entry into a control loss event is predicted to occur within the future-time prediction window. The predictive architecture is applied in simulation to the short period, roll, and dutch roll modes of a light business jet, and results demonstrate that the models are able to successfully predict, for various initial conditions and for various failure scenarios, the critical control limits that should not be exceeded in order to avoid entry into a control loss situation.
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Publisher
American Institute of Aeronautics and Astronautics, Inc.
Journal
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Series
AIAA Guidance, Navigation, and Control Conference
2018
2018