Real-time adaptive optimal prediction of safe control spaces and augmented-reality head-up displays towards aircraft loss-of-control mitigation
Steck, James E.
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Rafi, M., Steck, J. E., & Chakravarthy, A. (2021). Real-time adaptive optimal prediction of safe control spaces and augmented-reality head-up displays towards aircraft loss-of-control mitigation. Paper presented at the AIAA Scitech 2021 Forum, 1-26. doi.org/10.2514/6.2021-0757
Predictive systems capable of alerting pilots to impending entry into a loss-of-control event have potential to improve safety in flight. Towards this end, the General Aviation Flight Lab at Wichita State University has continued with the development and refinement of an early warning mechanism that predicts an aircraft’s “receding-horizon” safe control margins and alerts pilots to future impending excursion of its safe flight envelope. The concept's intent is to mitigate entry into loss-of-control by continually keeping an aircraft at a certain time-distance from the edge of its flight envelope. The adaptive prediction architecture utilizes a linear quadratic tracker to perform on-the-fly computations of critical control trajectories that would lead to control loss several seconds in the future. These critical control trajectories form the bounds of a three-dimensional safe control space that, if maintained, would assist a pilot in keeping an aircraft within its safe flight envelope. This safe control space is visually presented to the pilot through head-up augmented-reality displays, providing pre-emptive warning of impending entry into control loss and awareness of available remaining control authority at any given moment. An adaptive parameter estimation component is also implemented to enable real-time modeling error identification, accounting for uncertainties such as failures or modeling error in the aircraft. The architecture is applied to an 8th order light business jet model with dynamic coupling between the longitudinal and lateral/directional states. Results from desktop simulation demonstrate successful prediction of the safe control space that should not be exceeded in order to avoid near-term future entry into control loss.
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