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
Department, Program, or Center
Computer Engineering (KGCOE)
Ver Schneider, Karl, "Simulation of a neural network-driven fuzzy controller" (1995). Thesis. Rochester Institute of Technology. Accessed from
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