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A new algorithm for speed observer based on Model Reference Adaptive System (MRAS) is proposed for high performance induction motor drive. It uses stator current error based MRAS speed observer. The reference model of the stator current error based MRAS is the measured stator current components and the adaptive model is neuro-fuzzy based stator current observer. The adaptive model also needs the use...
In this paper, a high performance speed control approach using artificial neural networks (ANNs) and fuzzy logic for the field oriented induction motor (IM) is proposed. This control method is developed using model reference adaptive control (MRAC) to improve the performance of the IM speed. By using an adaptive neural network controller (ANNC) in the MRAC method, the speed of an IM can be controlled...
This paper presents a novel model reference adaptive system (MRAS) speed observer for induction motor drives based on stator currents. The measured currents are used as reference model for the MRAS observer to avoid the use of a pure integrator. A two layer Neural Network (NN) stator current observer is used as the adaptive model which requires the rotor flux information. This can be obtained from...
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