Design a PID controller of BLDC motor by using hybrid genetic-immune
In this paper hybridization between two optimization methods that are Genetic Algorithm (GA) and Artificial Immune System (AIS) is presented for determining the optimal proportional-integral derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The brushless DC mo...
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my.uniten.dspace-58262018-01-04T03:32:13Z Design a PID controller of BLDC motor by using hybrid genetic-immune Ali, M.O. Koh, S.P. Chong, K.H. Hamoodi, A.S. In this paper hybridization between two optimization methods that are Genetic Algorithm (GA) and Artificial Immune System (AIS) is presented for determining the optimal proportional-integral derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The brushless DC motor is modeled in Simulink and the Hybrid GA-AIS algorithm is implemented in MATLAB. The capability of overcoming the shortcomings of individual algorithms without losing their advantages makes the hybrid techniques superior to the stand-alone ones based on the dominant purpose of hybridization. The Hybrid GA-AIS method has superior features, stable convergence characteristic and good computational efficiency. The results that get it from hybridization are improved compares with that results can get from GA and AIS alone. The hybrid GA-AIS consists of two processes, the first one is a genetic algorithm (GA) is typically initialized population randomly. Hybridization is faster and more accurate compare with GA AIS alone. © Canadian Center of Science and Education. 2017-12-08T07:26:29Z 2017-12-08T07:26:29Z 2011 Article https://www.scopus.com/record/display.uri?eid=2-s2.0-79956305164&origin=resultslist&sort=plf-f&src=s&sid=38418e993e48c5d2470a09d70cf8abdc&sot en_US Modern Applied Science Volume 5, Issue 1, February 2011, Pages 75-85 |
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In this paper hybridization between two optimization methods that are Genetic Algorithm (GA) and Artificial Immune System (AIS) is presented for determining the optimal proportional-integral derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The brushless DC motor is modeled in Simulink and the Hybrid GA-AIS algorithm is implemented in MATLAB. The capability of overcoming the shortcomings of individual algorithms without losing their advantages makes the hybrid techniques superior to the stand-alone ones based on the dominant purpose of hybridization. The Hybrid GA-AIS method has superior features, stable convergence characteristic and good computational efficiency. The results that get it from hybridization are improved compares with that results can get from GA and AIS alone. The hybrid GA-AIS consists of two processes, the first one is a genetic algorithm (GA) is typically initialized population randomly. Hybridization is faster and more accurate compare with GA AIS alone. © Canadian Center of Science and Education. |
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Article |
author |
Ali, M.O. Koh, S.P. Chong, K.H. Hamoodi, A.S. |
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Ali, M.O. Koh, S.P. Chong, K.H. Hamoodi, A.S. Design a PID controller of BLDC motor by using hybrid genetic-immune |
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Ali, M.O. Koh, S.P. Chong, K.H. Hamoodi, A.S. |
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Ali, M.O. |
title |
Design a PID controller of BLDC motor by using hybrid genetic-immune |
title_short |
Design a PID controller of BLDC motor by using hybrid genetic-immune |
title_full |
Design a PID controller of BLDC motor by using hybrid genetic-immune |
title_fullStr |
Design a PID controller of BLDC motor by using hybrid genetic-immune |
title_full_unstemmed |
Design a PID controller of BLDC motor by using hybrid genetic-immune |
title_sort |
design a pid controller of bldc motor by using hybrid genetic-immune |
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2017 |
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1644493785609011200 |