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dc.contributor.advisorSteck, James E.
dc.contributor.advisorChakravarthy, Animesh
dc.contributor.authorRafi, Melvin
dc.date.accessioned2017-06-01T20:00:18Z
dc.date.available2017-06-01T20:00:18Z
dc.date.issued2017-04-28
dc.identifier.citationRafi, Melvin. 2017. Real-time predictive estimation of loss-of-control events on transport aircraft--In Proceedings: 13th Annual Symposium on Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p.71
dc.identifier.urihttp://hdl.handle.net/10057/13317
dc.descriptionPresented to the 13th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Rhatigan Student Center, Wichita State University, April 28, 2017.
dc.descriptionResearch completed in the Department of Aerospace Engineering, College of Engineering
dc.description.abstractLoss-of-Control events are the most significant contributing factor to accidents amongst commercial aircraft, and systems capable of warning pilots of impending entry into a control-loss event are crucial. To this extent, three look-ahead prediction architectures are designed to predict, in real-time, an aircraft's tendency to cross its control-loss boundaries. The algorithms continuously calculate the amount of control authority required to reach and exceed these boundaries over the course of a predefined future time period. These calculated control authority limits are visually presented to the pilot on an accompanying display, providing rapid alerts when impending entry into a control-loss event is predicted to occur in the upcoming several seconds. Validation of the algorithm's effectiveness is performed on the NASA Generic Transport Model, and the algorithm is successfully able to predict, at any given time, if the pilot's current input causes control-loss at 2 and 5 seconds in the future.
dc.description.sponsorshipGraduate School, Academic Affairs, University Libraries, Regional Institute on Aging
dc.language.isoen_US
dc.publisherWichita State University
dc.relation.ispartofseriesGRASP
dc.relation.ispartofseriesv. 13
dc.titleReal-time predictive estimation of loss-of-control events on transport aircraft
dc.typeAbstract
dc.rights.holderWichita State University


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