Machine Learning Structure for Controlling the Speed of Variable Reluctance Motor via Transitioning Policy Iteration Algorithm

This paper investigated a new speed regulator using an adaptive transitioning policy iteration learning technique for the variable reluctance motor (VRM) drive. A transitioning strategy is used in this unique scheme to handle the nonlinear behavior of the VRM by using a series of learning centers, e...

Full description

Bibliographic Details

Published in:	World electric vehicle journal Vol. 15; no. 9; p. 421
Main Author:	Alharkan, Hamad
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.09.2024
Subjects:	Adaptive algorithms adaptive control systems Algorithms Design optimization Dynamic programming Electric motors Iterative algorithms Machine learning machine learning method Methods Nonlinear control optimization problems Speed regulators Variable reluctance variable reluctance motor
ISSN:	2032-6653, 2032-6653
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!