International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Mar. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 85
Paper Published : 1402
No. of Authors : 3795
  Journal Paper

Paper Title
Neural Network based BLDC Motor Speed Control

Abstract
Brushless DC (BLDC) motors are widely used for many industrial applications because of their high efficiency, high torque and low volume. The aim of this research is to develop a complete model of the BLDC motor and to design an optimal controller for its speed control. Brushless DC (BLDC) motor control system is consisted of a multi-variable, non-linear, strong-coupling system, which is used to present robust and adaptive abilities. The interest in emerging intelligent controller for BLDC motor has been increased significantly. Neural Control is an ANN (Artificial Neural Network) based control method whereby the available data is the result of measuring the dynamic behavior of the system. This capability is well suited to be applied to adaptive control systems where the controller requires adaptation due to changes in system behavior. ANN was used to build the inverse model of BLDC motor speed control. This model was then used as controller. Keywords - BLDC Motor, BLDC Motor Speed, ANN, Neural Control.


Author - Nikhil S. Shelke, Sampath Kumar

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