Torque Ripple Minimization of Variable Reluctance Motor Using Reinforcement Dual NNs Learning Architecture

Torque Ripple Minimization of Variable Reluctance Motor Using Reinforcement Dual NNs Learning Architecture

The torque ripples in a switched reluctance motor (SRM) are minimized via an optimal adaptive dynamic regulator that is presented in this research. A novel reinforcement neural network learning approach based on machine learning is adopted to find the best solution for the tracking problem of the SR...

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Bibliographic Details
Main Author: Hamad Alharkan
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Energies
Subjects:
variable reluctance motor
optimization problems
reinforcement learning (RL)
adaptive dynamic programming (ADP)
neural network (NN)
machine learning method
Online Access:https://www.mdpi.com/1996-1073/16/13/4839

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