Speed Control for Multi-phase Induction Machine Fed by Multi-level Converters Using New Neuro-Fuzzy

  • E. Zaidi
  • K. Marouani
  • H. Bouadi
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)


This paper proposes a novel neuro-fuzzy control (NFC) for multi-phase induction machine (MPIM) fed by two multi-level converters (MLC) using venturing modulation algorithm. A four-layer artificial neural network (ANN) structure is utilized to train the parameters of the fuzzy logic controller (FLC) based on the minimization of the square of the error. In the proposed method indirect field oriented control (IFOC) is applied to the MPIM. The results are compared with the results obtained from a proportional–integral (PI) controller. Simulation results obtained are very satisfactory and showed that neuro-fuzzy control performance is enhanced using two multi-level converters (MLC) with introduces load disturbances.


Multi-phase induction machine (MPIM) Multi-level converters (MLC) Neuro-fuzzy controller (NFC) 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Ecole Militaire Polytechnique, LCM-UER-ELTBordj El-BahriAlgeria

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