This research documents the creation and use of an open-loop feed forward control scheme designed to manipulate the DC potential across lipid bilayer membranes in artificial hair cell sensors. Inspired by the human cochlea's non-linear gain phenomenon, whereby the cochlea can increase or decrease the effective gain of the auditory system, this controller is the first step in developing more sophisticated signal processing schemes for use with future bio-inspired artificial hair cell development. This open-loop controller allows for three preset gain mappings to tailor the DC offset in response to an external stimulus. Linear, nonlinear and sigmoidal mappings were created to observe the differences in system response during constant frequency and variable frequency excitation. In constant frequency testing, artificial hair cell sensors were excited at 100 Hz across a range of input intensities to observer current output response during increasing or decreasing excitation levels. Results showed average coherence values above 0.98 for the relationship between current output and fluid velocity, indicating a strong correlation between excitation and measured output. In the bilayer with stereocilia test case, RMS power increased with higher excitation levels but the various control laws did not appear to have any discernible impact on output power. In variable frequency testing, sensors were excited from 0-300 Hz to observe the real time effects of our control law on amplification or attenuation of output current with varying input intensity. Results of the variable frequency excitation could not definitively prove that the varied DC potential had an effect on current output due to excessive capacitive noise, but the controller did provide some encouraging results from its behavior during testing. We observed three distinct DC potential response curves for each mapping, indicating, that with some refinement, we should be able to manipulate output current with user defined gain tunings. / Master of Science
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/51611 |
Date | 11 March 2015 |
Creators | Crowley, Kevin Michael |
Contributors | Mechanical Engineering, Leo, Donald J., Grant, John Wallace, Tarazaga, Pablo Alberto |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Detected Language | English |
Type | Thesis |
Format | ETD, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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