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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-09-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/15/9/421 |