Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer
The need for tuning the PI controller is to improve its performance metrics such as rise time, settling time and overshoot. This paper proposed the Grey Wolf Optimizer (GWO) tuning method of a Proportional Integral (PI) controller for fixed speed Wind Turbine. The objective is to overcome the limita...
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Institute of Advanced Engineering and Science
2020
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Online Access: | http://eprints.utm.my/id/eprint/93351/1/AhmadSafawiMokhtar2020_OptimalTuningOfProportionalIntegralController.pdf http://eprints.utm.my/id/eprint/93351/ http://dx.doi.org/10.11591/IJECE.V10I5.PP5251-5261 |
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my.utm.933512021-11-30T08:21:31Z http://eprints.utm.my/id/eprint/93351/ Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer Hamza Sule, Aliyu Mokhtar, Ahmad Safawi Jamian, Jasrul Jamani Khidrani, Attaullah Larik, Raja Masood TK Electrical engineering. Electronics Nuclear engineering The need for tuning the PI controller is to improve its performance metrics such as rise time, settling time and overshoot. This paper proposed the Grey Wolf Optimizer (GWO) tuning method of a Proportional Integral (PI) controller for fixed speed Wind Turbine. The objective is to overcome the limitations in using the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) tuning methods for tuning the PI controller, such as quick convergence occurring too soon into a local optimum, and overshoot of the controller step input response. The GWO, the PSO, and the GA tuning methods were implemented in the Matlab 2016b to search the optimal gains of the Proportional and Integral controller through minimization of the objective function. A comparison was made between the results obtained using the GWO tuning method against PSO and GA tuning techniques. The GWO computed the smallest value of the minimized objective function. It exhibited faster convergence and better time response specification compared to other two methods. These and more performance indicators show the superiority of the GWO tuning method. Institute of Advanced Engineering and Science 2020 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/93351/1/AhmadSafawiMokhtar2020_OptimalTuningOfProportionalIntegralController.pdf Hamza Sule, Aliyu and Mokhtar, Ahmad Safawi and Jamian, Jasrul Jamani and Khidrani, Attaullah and Larik, Raja Masood (2020) Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer. International Journal of Electrical and Computer Engineering, 10 (5). pp. 5251-5261. ISSN 2088-8708 http://dx.doi.org/10.11591/IJECE.V10I5.PP5251-5261 |
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TK Electrical engineering. Electronics Nuclear engineering Hamza Sule, Aliyu Mokhtar, Ahmad Safawi Jamian, Jasrul Jamani Khidrani, Attaullah Larik, Raja Masood Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer |
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The need for tuning the PI controller is to improve its performance metrics such as rise time, settling time and overshoot. This paper proposed the Grey Wolf Optimizer (GWO) tuning method of a Proportional Integral (PI) controller for fixed speed Wind Turbine. The objective is to overcome the limitations in using the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) tuning methods for tuning the PI controller, such as quick convergence occurring too soon into a local optimum, and overshoot of the controller step input response. The GWO, the PSO, and the GA tuning methods were implemented in the Matlab 2016b to search the optimal gains of the Proportional and Integral controller through minimization of the objective function. A comparison was made between the results obtained using the GWO tuning method against PSO and GA tuning techniques. The GWO computed the smallest value of the minimized objective function. It exhibited faster convergence and better time response specification compared to other two methods. These and more performance indicators show the superiority of the GWO tuning method. |
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Article |
author |
Hamza Sule, Aliyu Mokhtar, Ahmad Safawi Jamian, Jasrul Jamani Khidrani, Attaullah Larik, Raja Masood |
author_facet |
Hamza Sule, Aliyu Mokhtar, Ahmad Safawi Jamian, Jasrul Jamani Khidrani, Attaullah Larik, Raja Masood |
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Hamza Sule, Aliyu |
title |
Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer |
title_short |
Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer |
title_full |
Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer |
title_fullStr |
Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer |
title_full_unstemmed |
Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer |
title_sort |
optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer |
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Institute of Advanced Engineering and Science |
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2020 |
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http://eprints.utm.my/id/eprint/93351/1/AhmadSafawiMokhtar2020_OptimalTuningOfProportionalIntegralController.pdf http://eprints.utm.my/id/eprint/93351/ http://dx.doi.org/10.11591/IJECE.V10I5.PP5251-5261 |
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