Using Wavelet Based Neural Networks for Feedback Signals Estimation of a Vector Controlled Induction Motor Drive

  • Authors:

  • Hassan Moghbelli;Akbar Rahideh;Ali A Safavi

  • Affiliations:

  • Science and Mathematics, Texas A&M University at Qatar, Doha, Qatar;School of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran;School of Engineering, Shiraz University, Shiraz, Iran

  • Venue:
  • ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
  • Year:
  • 2009

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Abstract

In this investigation, a vector controlled induction motor drive is simulated and the feedback signals of this vector controlled drive are estimated using neural networks. The neural networks receive the machine terminal signals as inputs and estimate the rotor flux and unit vectors cos*** e and sin*** e as outputs. These outputs are used in the vector controlled drive system. The calculated feedback signals by the neural networks are not sensitive to the motor parameter variations. In this paper, three types of neural networks (i.e. multilayer perceptron (MLP), radial basis function (RBF) and wavenet) are used and the obtained results are compared. Finally, on the basis of the advantages of wavenets, the results prove the accuracy and effectiveness of the wavenet based estimator.