Methodology for Dynamic Data-Driven Online Flight Capability Estimation
Name
Willcox_Methodology for Dynamic.pdf
Size
1.79 MB
Format
Adobe PDF
Checksum (MD5)
5a7c0f3a59da0f255b04a5fe6d1c3363
Author(s)
Allaire, Douglas
Lecerf, Marc A.
Willcox, Karen E
Date Issued
October 2015
Journal
AIAA Journal
Publisher
American Institute of Aeronautics and Astronautics
Citation
Lecerf, Marc, Douglas Allaire, and Karen Willcox. “Methodology for Dynamic Data-Driven Online Flight Capability Estimation.” AIAA Journal 53.10 (2015): 3073–3087.
Version
Author's final manuscript
Abstract
This 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.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.2514/1.j053893
