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2014 (Vol. 7, Issue: 8)
Article Information:

New Optimized Soft Computing Speed Controller for PMSM Drive

A. El Janati El Idrissi, N. Zahid and M. Jedra
Corresponding Author:  A. El Janati El Idrissi 

Key words:  Direct torque control, extended kalman filter, genetic algorithm, permanent magnet synchronous motor, recurrent neural network, space vector modulation,
Vol. 7 , (8): 1582-1586
Submitted Accepted Published
May 17, 2013 June 14, 2013 February 27, 2014

This study proposes a soft computing speed controller where recurrent neural network speed controller is trained by genetic extended kalman filter, based on a predetermined genetic Proportional Integral (PI) controller. A genetic PI gives to this proposed speed controller exact values without mathematical equations, unlike the classical PI who is need for it necessary. With this proposed method the results of simulation obtained is as they are of real state of the Permanent Magnet Synchronous Motor (PMSM). The harmonic ripples of speed response are also minimized with Genetic Extended Kalman Filter (GEKF) and Neural Network Space Vector Modulation (NNSVM). This fusion between the Artificial Intelligence (AI) and optimized method of the extended kalman filter gives more superiority to the method proposed, like shows the simulations results compared to classical Neural Network Controller (NNC).
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  Cite this Reference:
A. El Janati El Idrissi, N. Zahid and M. Jedra, 2014. New Optimized Soft Computing Speed Controller for PMSM Drive.  Research Journal of Applied Sciences, Engineering and Technology, 7(8): 1582-1586.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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