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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Main Authors: Hamza Sule, Aliyu, Mokhtar, Ahmad Safawi, Jamian, Jasrul Jamani, Khidrani, Attaullah, Larik, Raja Masood
Format: Article
Language:English
Published: 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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Institution: Universiti Teknologi Malaysia
Language: English
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spelling 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
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle 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
description 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.
format 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
author_sort 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
publisher Institute of Advanced Engineering and Science
publishDate 2020
url 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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