• Jul 12, 2018 News!The submission for 2019 8th International Conference on Information and Electronics Engineering (ICIEE 2019) is officially open now !   [Click]
  • Dec 11, 2018 News!IJIEE Vol. 8, No. 4 issue has been published online!   [Click]
  • Aug 31, 2018 News!IJIEE Vol. 8, No. 3 issue has been published online!   [Click]
General Information
    • ISSN: 2010-3719
    • Frequency: Quarterly
    • DOI: 10.18178/IJIEE
    • Editor-in-Chief: Prof. Chandratilak De Silva Liyanage
    • Associate Executive Editor: Ms. Jennifer Zeng
    • Executive Editor: Mr. Ron C. Wu
    • Abstracting/ Indexing : Google Scholar, Electronic Journals Library, Crossref and ProQuest, Ei (INSPEC, IET).
    • E-mail ijiee@ejournal.net

Faculty of Science, University of Brunei Darussalam, Brunei Darussalam   
" It is a great honor to serve as the editor-in-chief of IJIEE. I'll work together with the editorial team. Hopefully, IJIEE will be recognized among the readers in the related field."
IJIEE 2013 Vol.3(2): 191-195 ISSN: 2010-3719
DOI: 10.7763/IJIEE.2013.V3.296

Solving Harmonic Elimination Equations in Multi-Level Inverters by Using Neural Networks

O. Bouhali, F Bouaziz, N. Rizoug and A. Talha

Abstract—Pulse Width Modulation (PWM) using the harmonic elimination technique needs the solving of a nonlinear transcendental equations system. Conventionally, due to their high complexity, these equations have to be solved off-line and the calculated optimal switching angles are stored in look-up tables or interpolated by simple functions for real-time operation. System flexibility is very limited, especially for applications which require both amplitude and frequency control. A new implementation scheme based on real-time solving of the nonlinear harmonic elimination equations using feed forward Artificial Neural Networks (ANNs) is reported in this paper. Based on the well known Back-propagation Algorithm (BPA), two training schemes for the ANN are presented. In the first one, the ANN is trained using the desired switching angles given by the classical method. The second training scheme is developed using only the harmonic elimination equation systems. Some simulation results are given to show the feasibility, performances and technical advantages of the proposed method.

Index Terms—Artificial neural networks, solving algorithm, harmonic elimination algorithm, multilevel inverter.

O. Bouhali and F. Fatiha are with Mecatronic Laboratory, Jijel University, Algeria (email: bouhali_omar@univ-jijel.dz).
N. Rizoug is with the Ecole Supérieure des Techniques Aéronautiques et de Construction Automobile (ESTACA) (e-mail: nassim.rizoug@estaca.fr).
A. Talha is with the Electrical Engineering Department of University of Science and Technology Houari Boumediene (e-mail: abtalha@gmail.com).


Cite: O. Bouhali, F Bouaziz, N. Rizoug and A. Talha, "Solving Harmonic Elimination Equations in Multi-Level Inverters by Using Neural Networks," International Journal of Information and Electronics Engineering vol. 3, no. 2, pp. 191-195, 2013.

Copyright © 2008-2018. International Journal of Information and Electronics Engineering. All rights reserved.
E-mail: ijiee@ejournal.net