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Article Information:
Speed Control of a DC Motor for the Orientation of a Heliostat in a Solar Tower Power Plant using Artificial Intelligence Systems (FLC and NC)
Abdelfettah Zeghoudi and Ali Chermitti
Corresponding Author: Abdelfettah Zeghoudi
Submitted: January 8, 2015
Accepted: February 5, 2015
Published: June 15, 2015 |
Abstract:
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Recent research in the field of motor controls is becoming more interesting especially with the developments of new control methods. This study shows a comparative study between two artificial intelligence methods namely neural networks and fuzzy logic for the speed control of a DC motor for the orientation of a heliostat in a solar tower power plant. The speed controller of DC motor is performed using two Fuzzy Logic Configuration (FLC1 and FLC2) and neural controller in MATLAB environment. The simulation results are used to make sure the real possibility of using artificial intelligence systems to identify and control this type of installation. The performance of the Fuzzy Logic Controller and Neural control are compared using different errors metrics. The results show that Fuzzy logic method is more efficient compared with neural controller method.
Key words: Artificial intelligence, DC motor, Fuzzy Logic, heliostat, neural controller, solar tower power plant, speed control
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Cite this Reference:
Abdelfettah Zeghoudi and Ali Chermitti, . Speed Control of a DC Motor for the Orientation of a Heliostat in a Solar Tower Power Plant using Artificial Intelligence Systems (FLC and NC). Research Journal of Applied Sciences, Engineering and Technology, (5): 570-580.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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