Abstract

A software simulation package was developed to facilitate the analysis of a fuzzy logic tracking system constructed by first training a neural network. The adaptive vector quantization neural network used a competitive learning algorithm to classify control data from a controller in a noisy environment. The neural network memory generated rules for a fuzzy controller by mapping the state of the network into a predetermined fuzzy database. The software is intended to be expanded to allow further analysis of neural dynamics and to compare the performance of the resulting fuzzy controller to conventional controllers.

Library of Congress Subject Headings

Neural networks (Computer science); Fuzzy systems; Automatic control

Publication Date

10-1-1995

Document Type

Thesis

Department, Program, or Center

Computer Engineering (KGCOE)

Advisor

Chang, Tony

Advisor/Committee Member

Anderson, Peter

Advisor/Committee Member

Brown, George

Comments

Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works. Physical copy available through RIT's The Wallace Library at: QA76.87 .V465 1995

Campus

RIT – Main Campus

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