Holdings: Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning

Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning

An improved fractional-order sliding mode control (FOSMC) for PMSM is presented in this study to set the unavoidable parameters and to improve permanent magnet synchronous motors (PMSMs) drive performance, such as current and speed tracking accuracy. To determine the optimal parameters of the FOSMC...

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Bibliographic Details
Main Authors:	Zahraoui Y., Zaihidee F.M., Kermadi M., Mekhilef S., Alhamrouni I., Seyedmahmoudian M., Stojcevski A.
Other Authors:	57223913703
Format:	Article
Published:	MDPI 2024
Subjects:	artificial neural network feedback linearization fractional-order sliding mode control nonlinear disturbance observer PMSM drive reinforcement learning Controllers Errors Learning algorithms Learning systems Neural networks Parameter estimation Permanent magnets Reinforcement learning Sliding mode control Speed control Synchronous motors Two term control systems Disturbance observer Feedback linearisation Fractional order Fractional-order sliding mode control Nonlinear disturbance Nonlinear disturbance observer Permanent Magnet Synchronous Motor Permanent-magnet synchronous motor drives Reinforcement learnings Sliding-mode control Feedback linearization
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Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning

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