Show simple item record

dc.contributor.authorAllaire, Douglas
dc.contributor.authorLecerf, Marc A.
dc.contributor.authorWillcox, Karen E
dc.date.accessioned2017-01-11T21:09:29Z
dc.date.available2017-01-11T21:09:29Z
dc.date.issued2015-10
dc.date.submitted2015-04
dc.identifier.issn0001-1452
dc.identifier.issn1533-385X
dc.identifier.urihttp://hdl.handle.net/1721.1/106347
dc.description.abstractThis paper presents a data-driven approach for the online updating of the flight envelope of an unmanned aerial vehicle subjected to structural degradation. The main contribution of the work is a general methodology that leverages both physics-based modeling and data to decompose tasks into two phases: expensive offline simulations to build an efficient characterization of the problem and rapid data-driven classification to support online decision making. In the approach, physics-based models at the wing and vehicle level run offline to generate libraries of information covering a range of damage scenarios. These libraries are queried online to estimate vehicle capability states. The state estimation and associated quantification of uncertainty are achieved by Bayesian classification using sensed strain data. The methodology is demonstrated on a conceptual unmanned aerial vehicle executing a pullup maneuver, in which the vehicle flight envelope is updated dynamically with onboard sensor information. During vehicle operation, the maximum maneuvering load factor is estimated using structural strain sensor measurements combined with physics-based information from precomputed damage scenarios that consider structural weakness. Compared to a baseline case that uses a static as-designed flight envelope, the self-aware vehicle achieves both an increase in probability of executing a successful maneuver and an increase in overall usage of the vehicle capability.en_US
dc.description.sponsorshipUnited States. Air Force Office of Scientific Research. Dynamic Data-Driven Application Systems Program (Grant FA9550-11-1-0339)en_US
dc.language.isoen_US
dc.publisherAmerican Institute of Aeronautics and Astronauticsen_US
dc.relation.isversionofhttp://dx.doi.org/10.2514/1.j053893en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleMethodology for Dynamic Data-Driven Online Flight Capability Estimationen_US
dc.typeArticleen_US
dc.identifier.citationLecerf, Marc, Douglas Allaire, and Karen Willcox. “Methodology for Dynamic Data-Driven Online Flight Capability Estimation.” AIAA Journal 53.10 (2015): 3073–3087.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.mitauthorLecerf, Marc A.
dc.contributor.mitauthorWillcox, Karen E
dc.relation.journalAIAA Journalen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsLecerf, Marc; Allaire, Douglas; Willcox, Karenen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-2156-9338
mit.licenseOPEN_ACCESS_POLICYen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record