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  4. Reference Model BLDC Motor Speed Control Using Neural Adaptive Control
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Category: MTech Power Systems Projects
By MTech Projects
MTech Projects
16.Nov
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Reference Model BLDC Motor Speed Control Using Neural Adaptive Control

PROJECT TITLE :

Model Reference Neural Adaptive Control Based BLDC Motor Speed Control

ABSTRACT:

A multi-variable, non-linear, strong-coupling system is employed in the brushless DC (BLDC) motor control system to show resilient and adaptable capabilities. The interest in the new intelligent controller for BLDC motors has risen dramatically in recent years. An ANN (Artificial Neural Network)-based control technology, neural control makes use of data gleaned through monitoring the system's dynamic behaviour. Adaptive control systems can benefit from this feature because the controller must be reprogrammed when the system's behaviour changes. A neural network (ANN) was utilised to create an inverse model of BLDC motor speed. The controller was then based on this model. The MRAC concept was used to develop control schemes with good dynamic reactions.

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Previous article: Bidirectional DCDC Converters and ACDC Interlinking Converter Model Predictive Control Bidirectional DCDC Converters and ACDC Interlinking Converter Model Predictive Control Next article: Simulation And Modeling Of A Single Side Short Stator Linear Induction Motor With The End Effect Simulation And Modeling Of A Single Side Short Stator Linear Induction Motor With The End Effect
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