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

• 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

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...