Development and Implementation of a Speed Sensorless Induction Motor Drives Using an Adaptive Neuro – Fuzzy Flux Observer
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In this paper, we propose an adaptive neuro-fuzzy inference system for high performance induction motor drive. The simultaneous observation of rotor speed and stator resistance in induction drive is obtained through a neuro-fuzzy observer trained with a backpropagation algorithm. The dynamic performance and robustness of the proposed neuro-fuzzy adaptive observer are evaluated under a variety of operation conditions. The suggested approach is designed and implemented in the laboratory and its effectiveness in tracking application is verified. Experimental results have shown excellent tracking performance of the proposed speed sensorless control system and have convincingly demonstrated the usefulness of the hybrid neuro-fuzzy flux observer in high performance drives with uncertainties
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