A Comparative Study of Neural Networks and Fuzzy Systems in Modeling of a Nonlinear Dynamic System
Makaleler > Tam Makale · 2011
Yazarlar: Metin DEMIRTAS, Musa ALCI
An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Uluslararası, 2011, cilt 1
DOI: 10.11121/ijocta.01.2011.00055
Özet
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.