Abstract
The aim of this paper is to compare the neural network and fuzzy modeling approaches on a nonlinear system. We have taken Permanent Magnet Brushless Direct Current (PMBDC) motor data and have generated models using both approaches. The predictive performance of both methods was compared on the data set for model configurations.The paper describes the results of these tests and discusses the effects of changing model parameters on predictive and practical performance. Modeling sensitivity was used to compare for two methods.
Publisher
International Journal of Optimization and Control: Theories and Applications
Subject
Applied Mathematics,Control and Optimization
Cited by
2 articles.
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