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A Neuro-Fuzzy Controller for Doubly FED Asynchronous Motor Drive

Azeddine Chaiba*, Rachid Abdessemed**, M. Lokmen Bendass***

* Department of Electrical Engineering, Faculty of Technology, University of Setif, Algeria.

**,*** LEB Research Laboratory, University of Batna, Algeria.

Periodicity:July - September'2010
DOI : https://doi.org/10.26634/jee.4.1.1246

Abstract

In this paper neuro-fuzzy controller for Doubly Fed Asynchronous Motor (DFAM) drive is proposed. First, a mathematical model of DFAM written in an appropriate d-q reference frame is established to investigate simulations. In order to control the rotor currents of DFAM, a torque tracking control law is synthesized using PI controllers, under conditions of the stator side power factor is controlled at unity level. A four layer Neural Network (NN) is used to adjust input and output parameters of membership functions in a fuzzy logic controller (FLC). The back propagation learning algorithm is used for training this network. The performances of neuro-fuzzy controller (NFC) which is based on the torque tracking control algorithm are investigated and compared to those obtained from the PI controller. Results obtained in Matlab/Simulink environment show that the NFC is more robust, superior dynamic performance and hence found to be a suitable replacement of the conventional PI controller for the high performance drive applications.

Keywords

Doubly-Fed Asynchronous Motor (DFAM), Torque Tracking Control, Neuro-Fuzzy controller

How to Cite this Article?

Azeddine Chaiba, Rachid Abdessemed and M. Lokmen Bendaas (2010). A Neuro-Fuzzy Controller For Doubly Fed Asynchronous Motor Drive. i-manager’s Journal on Electrical Engineering, 4(1), 8-15. https://doi.org/10.26634/jee.4.1.1246

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