The neural network control approach for PMSM based on a high gain observer

This article mainly explores a new control method for permanent magnet synchronous motor (PMSM) based on a BP neural network and a high gain observer. Different from the back-stepping schemes, a high-gain observer is applied to estimate the error and speed, a BP neural network is utilized to control the current and a linear feedback controller is designed to control the motor speed. Therefore, there is no need to build a complicated virtual controller, which greatly simplifies the design of the controller and reduces the calculation burden of the neural network. Finally, simulation results demonstrate the effectiveness of the proposed method.

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