Control of Permanent Magnet Synchronous Motor

Mosleh Maeid Al-Harthi


This paper deals with the use of neural network methods to perform control of Permanent Magnet synchronous Motors (PMSM). The traditional Proportional-Integral- Derivative (PID) controller is largely used in industry because of the robustness that procures this regulator. When the dynamics of the system vary over time or with operating conditions, the PID controller became not available. The Artificial Neural Networks (ANN) used as a speed controller seems to be promising solutions to achieve the required performance. In this study we apply neural networks regulator in place of Pl controller of the field-oriented control scheme of the PMSM. The simulation results obtained demonstrate the efficiency of the proposed controller to ensure the required performance.



Permanent Magnet Synchronous Motor; Artificial Neural Network; Levenberg-Marquardt; Speed Control.

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