This thesis describes a new technique, known as direct trajectory sampling, for extracting
aerodynamic coefficients directly from Micro Air Vehicle trajectory data. The experiment
is conducted in the Interactive Guidance and Control Laboratory (Aerospace Engineering &
Mechanics, University of Minnesota) using the vision tracking system and an aircraft fitted
with reflective markers on its wings, fuselage, nose and tail. The technique was developed to
study the aerodynamics of small-scale aircraft as the traditional methods using wind tunnels
and computational fluid dynamics have produced limited results for this rapidly growing
field of research.
The indoor environment takes advantage of the stationary atmospheric conditions and as
the glider is launched into flight the full trajectory is captured by the tracking system while
the aircraft position and attitude vary naturally throughtout the flight. The experimental
data is filtered with a Kalman filter to eliminate any data drop-outs and to generate velocities
and accelerations. Aerodynamic forces, moments and angles are extracted from the filtered
flight data and are used in the calculation of the aerodynamic coefficients.
Stability derivatives are determined from the aerodynamic coefficients using a linear regression
approach, and these are then refined with a flight simulation model and the technique
of maximum likelihood estimation. Once the stability derivatives have been refined, resulting
in an identified system, the aircraft simulation model is validated using the weighted
mean of each stability derivative. Pleasing results are obtained in several cases but further
refinement of the model is required before confident claims regarding the validation can be
University of Minnesota M.S. thesis. December 2010. Major: Aerospace Engineering and Mechanics. Advisor:Professor
Bernie Mettler. 1 computer file (PDF); xvii, 98 pages. Ill. (some col.)
Woollands, Robyn Michèle.
System identification modeling of micro air vehicles from visual motion tracking data..
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