DIRECT TORQUE NEURO FUZZY SPEED CONTROL OF AN INDUCTION MACHINE DRIVE BASED ON A NEW VARIABLE GAIN PI CONTROLLER

Eid Al-radadi

   This paper presents an original variable gain PI (VGPI) controller for speed control of a simplified direct torque neuro fuzzy controlled (DTNFC) induction motor drive. First, a simplified direct torque neuro fuzzy control (DTNFC) for a voltage source PWM inverter fed induction motor drive is presented. This control scheme uses the stator flux amplitude and the electromagnetic torque errors through a four rules adaptive NF inference system (ANFIS) to generate a voltage space vector (reference voltage). This voltage is used by a space vector modulator to generate the inverter switching states. Then a VGPI controller is designed in order to be used as the speed controller in the simplified DTNFC induction motor drive. Simulation of the simplified DTNFC induction motor drive using VGPI for speed control shows promising results. The motor reaches the reference speed rapidly and without overshoot, load disturbances are rapidly rejected and the detuning problem caused by the stator resistance variation is fairly well dealt with.

Keywords: induction motor, direct torque control, direct torque neuro fuzzy control, adaptive NF inference system, variable gain PI controller, space vector modulation

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