A simplified speed controller for direct torque neuro fuzzy controlled induction machine drive based on a variable gain PI controller

Abstract

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 an adaptive NF inference system (ANFIS) to generate a voltage space vector (reference voltage) which is used by a space vector modulator to generate the inverter switching states. In this paper a four rules ANFIS structure is proposed. This structure generates the desired reference voltage by acting on both the amplitude and the angle of its components. 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.