Optimal Tracking Current Control of Switched Reluctance Motor Drives Using Reinforcement Q-Learning Scheduling

Optimal Tracking Current Control of Switched Reluctance Motor Drives Using Reinforcement Q-Learning Scheduling

In this article, a novel Q-learning scheduling method for the current controller of a switched reluctance motor (SRM) drive is investigated. The Q-learning algorithm is a class of reinforcement learning approaches that can find the best forward-in-time solution of a linear control problem. An augmen...

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Bibliographic Details
Main Authors: Hamad Alharkan, Sepehr Saadatmand, Mehdi Ferdowsi, Pourya Shamsi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Adaptive dynamic programming
current control
least square methods
motor drive
optimal control
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/9317726/

Internet

https://ieeexplore.ieee.org/document/9317726/

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