Abstract
This paper presents a novel space vector pulse-width modulated vector controlled induction motor drive with adaptive neuro-fuzzy based speed controller. SVPWM is superior to other PWM schemes from the view point of dc-link voltage utilization and current harmonics. The proposed neuro-fuzzy controller incorporates fuzzy logic algorithm with a five-layer artificial neural network (ANN) structure. The conventional PI controller is replaced by Adaptive Neuro-Fuzzy Inference System (ANFIS), which tunes the fuzzy inference system with hybrid learning algorithm. This makes fuzzy system to learn. The performance of the proposed neuro-fuzzy based SVPWM-VCIM drive is investigated at different operating conditions. The results of the proposed controller are also compared to those obtained by a conventional PI controller. The simulation study indicates robustness and suitability of drive for high performance drive applications. Keywords—Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), Space Vector Pulse-Width Modulation (SVPWM), hybrid learning algorithm, Vector Controlled Induction Motor (VCIM).
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