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Mathematical Problems in Engineering - Volume 2014 2014, Article ID 432593, 10 pages -

Research Article

Postgraduate Program in Electrical and Computer Engineering PPgEEC, LACI-DEE, Federal University of Rio Grande do Norte, 59078-970 Natal, RN, Brazil

The Computer Science Institute at the Federal University of Alagoas UFAL, 57072-900 Maceió, AL, Brazil

Department of Electrical Engineering DEE, Federal University of Rio Grande do Norte, 59078-970 Natal, RN, Brazil

Received 5 December 2013; Revised 19 February 2014; Accepted 12 March 2014; Published 30 April 2014

Academic Editor: Chien-Yu Lu

Copyright © 2014 Joilson Batista de Almeida Rego et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents an artificial intelligence application using a nonconventional mathematical tool: the radial basis function RBF networks, aiming to identify the current plant of an induction motor or other nonlinear systems. Here, the objective is to present the RBF response to different nonlinear systems and analyze the obtained results. A RBF network is trained and simulated in order to obtain the dynamical solution with basin of attraction and equilibrium point for known and unknown system and establish a relationship between these dynamical systems and the RBF response. On the basis of several examples, the results indicating the effectiveness of this approach are demonstrated.

Author: Joilson Batista de Almeida Rego, Allan de Medeiros Martins, and Evandro de B. Costa



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