John C. Gallagher (Advisor), Michael Raymer (Committee Member), Mateen M. Rizki (Committee Member)
Master of Science in Computer Engineering (MSCE)
The control of insect-sized flapping-wing micro air vehicles is fraught with difficulties. Even when adequate control laws are known, limits on computational precision and floating-point processing can render it difficult to field implementations that provide sufficiently accurate and precise vehicle body placement and pose. Augmentation of an existing altitude controller with an Evolvable Adaptive Hardware (EAH) oscillator has been proposed as a means for an on-board altitude controller to correct control precision and accuracy difficulties during normal flight. This thesis examines a range of setting of the internal learning algorithms for the EAH oscillator and provides empirical evidence about which setting are most optimal for the control of a flapping-wing micro air vehicle (FW-MAV) based on the Harvard MicroFly. Implications for future multi-degree of freedom control are also considered.
Department or Program
Department of Computer Science and Engineering
Year Degree Awarded
Copyright 2010, all rights reserved. This open access ETD is published by Wright State University and OhioLINK.