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Artificial Neural Network Control of Permanent Magnet Synchronous Motor

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 37 - Number 5
Year of Publication: 2012
Mahmoud. M. Saafan
Amira.Y. Haikal

Mahmoud. M Saafan, Amira.Y. Haikal, Sabry.F.Saraya and Fayez.F.G.Areed. Article: Artificial Neural Network Control of Permanent Magnet Synchronous Motor. International Journal of Computer Applications 37(5):9-18, January 2012. Full text available. BibTeX

	author = {Mahmoud. M. Saafan and Amira.Y. Haikal and Sabry.F.Saraya and Fayez.F.G.Areed},
	title = {Article: Artificial Neural Network Control of Permanent Magnet Synchronous Motor},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {37},
	number = {5},
	pages = {9-18},
	month = {January},
	note = {Full text available}


This paper presents a neural network controller for permanent magnet synchronous motor (PMSM). The neural controller is used for torque ripple minimization of this type of motors. Two methods of neural controller design are used. The first method is based on two loop controllers (current controller and speed controller). The second method is based on estimation of torque constant and stator resistance in PMSM. The q-axis inductance is modeled off-line according to q-axis stator current. The neural weights are initially chosen small randomly and a model reference control algorithm adjusts those weights to give the optimal values. The neural network parameter estimator has been applied to flux linkage torque ripple minimization of the PMSM. Simulation results using the two methods are compared together. Moreover, the suggested algorithms when compared with other controllers show great success in torque ripples reduction.


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