Enhancement of motor speed identification using artificial neural networks
Abstract
In this study have been utilized a modified version of ant colony optimization to improve the thresholds of neural networks and weights by including therank-weight approach. Furthermore, this technique easily overcome the drawbacks speed up convergence into the minimum while training the backpropagation neural network. The improved ant colony optimization-backpropagation neural.not only has the capacity to map extensively, but it also enhances operating efficiency noticeably, according to the simulation findings. The simulation results revealed that the speed sensor replaced with the ant colony optimization rw-optimized back propagation neural network-speed identification and motor’s speed determined using this approach the result is satisfactory.
Keywords
Ant colony algorithm; Back propagation; Direct torque control; Neural network; Speed identification
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PDFDOI: http://doi.org/10.11591/ijeecs.v27.i3.pp1388-1396
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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).