A Fuzzy-Based Controller of a Modified Six-Phase Induction Motor Driving a Pumping System

  • Mohamed I. AbdelwanisEmail author
  • Ragab A. El-Sehiemy
Research Paper


This study presents the implementation and analysis of the modified six-phase induction motor (IM) that drives a centrifugal pumping system. The three-phase IM is modified to operate as a six-phase IM to enhance the torque pulsation and to increase the motor reliability. Dynamic models of six-phase IM are derived. A fuzzy-based procedure for fine-tuning of the PID controller parameters is proposed in order to sustain the motor speed at the predefined reference values. Added to that, a six-phase low-pass filter is designed to eliminate the undesirable harmonics contents. An optimized PID controller accomplished with a scalar V/f closed-loop six-phase induction motor control is presented and its simulation results are discussed. Pulse width modulation (PWM)-based simulation studies were employed for six-phase induction motor using MATLAB/SIMULINK software. The simulation results show that the PWM inverter reduces the THD for current and voltage waveforms and the overall performance of the modified six-phase IM is enhanced compared with the equivalent three-phase induction motor.


Six-phase induction motor Sensorless speed Centrifugal pump PWM Harmonic distortion 

List of symbols


Inertia of the system, kg m2




Total pumping head, m


Flow rate, m3/h


Hydraulic power of pump, W

Rs, Rr

Stator and rotor resistances, Ω


Angular speed of arbitrary frame


Angular speed of rotor frame

Ids, Iqs

Direct and quadrature axis stator current, A

Lls, Llr

Stator and rotor inductance of motor, respectively, H


Magnetization inductance, H


Number of pole pairs


Electromagnetic torque of the motor, N m


Constant torque of the pump, N m

Vds, Vqs

Direct and quadrature component of stator voltage, V


Terminal voltage of the array, V

ψds, ψqs

Direct and quadrature component of stator flux


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Copyright information

© Shiraz University 2018

Authors and Affiliations

  1. 1.Intelligent Systems Research Group (ISRG), Electrical Engineering Department, Faculty of EngineeringKafrelsheikh UniversityKafrelsheikhEgypt

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