Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm

The stochastic nature of wind speed and turbulence between turbines commonly stress wind turbines, emphasizing the importance of regulating rotor speed based on desired reference speed. Employing a PID-based controller is crucial for wind turbine system performance. Recent interest in optimizing PID...

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Main Authors: Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari
Format: Conference or Workshop Item
Language:English
Published: IEEE 2024
Subjects:
Online Access:https://umpir.ump.edu.my/id/eprint/45400/
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author Islam, Muhammad Shafiqul
Mohd Ashraf, Ahmad
Mohd Riduwan, Ghazali
Mohd Helmi, Suid
Mohd Zaidi, Mohd Tumari
author_facet Islam, Muhammad Shafiqul
Mohd Ashraf, Ahmad
Mohd Riduwan, Ghazali
Mohd Helmi, Suid
Mohd Zaidi, Mohd Tumari
author_sort Islam, Muhammad Shafiqul
building UMP Institutional Repository
collection Online Access
description The stochastic nature of wind speed and turbulence between turbines commonly stress wind turbines, emphasizing the importance of regulating rotor speed based on desired reference speed. Employing a PID-based controller is crucial for wind turbine system performance. Recent interest in optimizing PID control parameters offers advantages in output response enhancement while preserving robustness and simplicity. However, existing optimization tools, especially those using multi-agent optimization, often entail a high computational burden due to a large number of function evaluations (NFE). This study presents a novel approach employing a safe experimentation dynamics algorithm (SEDA) to tune PID controllers in wind turbine systems. SEDA, a single-agent based optimization technique, requires only one function evaluation per iteration, alleviating computational burdens. Simulation analyses, encompassing convergence curves of the fitness function, time response specification analysis of step response, stability analysis using Bode plots, and computational effort analysis based on NFE, evaluate the effectiveness of the proposed SEDA-based PID controller for wind turbine systems Furthermore, the study reveals that the settling time (Ts) and percentage of overshoot (Mp) are notably low, measuring 1.27E-4s and 0%, respectively, compared to other algorithms. These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.
first_indexed 2025-11-15T04:00:13Z
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institution Universiti Malaysia Pahang
institution_category Local University
language English
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publishDate 2024
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spelling ump-454002025-08-15T02:24:40Z https://umpir.ump.edu.my/id/eprint/45400/ Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm Islam, Muhammad Shafiqul Mohd Ashraf, Ahmad Mohd Riduwan, Ghazali Mohd Helmi, Suid Mohd Zaidi, Mohd Tumari TK Electrical engineering. Electronics Nuclear engineering The stochastic nature of wind speed and turbulence between turbines commonly stress wind turbines, emphasizing the importance of regulating rotor speed based on desired reference speed. Employing a PID-based controller is crucial for wind turbine system performance. Recent interest in optimizing PID control parameters offers advantages in output response enhancement while preserving robustness and simplicity. However, existing optimization tools, especially those using multi-agent optimization, often entail a high computational burden due to a large number of function evaluations (NFE). This study presents a novel approach employing a safe experimentation dynamics algorithm (SEDA) to tune PID controllers in wind turbine systems. SEDA, a single-agent based optimization technique, requires only one function evaluation per iteration, alleviating computational burdens. Simulation analyses, encompassing convergence curves of the fitness function, time response specification analysis of step response, stability analysis using Bode plots, and computational effort analysis based on NFE, evaluate the effectiveness of the proposed SEDA-based PID controller for wind turbine systems Furthermore, the study reveals that the settling time (Ts) and percentage of overshoot (Mp) are notably low, measuring 1.27E-4s and 0%, respectively, compared to other algorithms. These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods. IEEE 2024-08 Conference or Workshop Item PeerReviewed pdf en https://umpir.ump.edu.my/id/eprint/45400/1/Data-driven%20PID%20controller%20of%20wind%20turbine%20systems.pdf Islam, Muhammad Shafiqul and Mohd Ashraf, Ahmad and Mohd Riduwan, Ghazali and Mohd Helmi, Suid and Mohd Zaidi, Mohd Tumari (2024) Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm. In: 2024 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2024 , 6 - 7 July 2024 , Kuala Lumpur. pp. 1-5.. ISBN 979-835038686-8 (Published) https://doi.org/10.1109/ISIEA61920.2024.10607295
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Islam, Muhammad Shafiqul
Mohd Ashraf, Ahmad
Mohd Riduwan, Ghazali
Mohd Helmi, Suid
Mohd Zaidi, Mohd Tumari
Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
title Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
title_full Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
title_fullStr Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
title_full_unstemmed Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
title_short Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
title_sort data-driven pid controller of wind turbine systems using safe experimentation dynamics algorithm
topic TK Electrical engineering. Electronics Nuclear engineering
url https://umpir.ump.edu.my/id/eprint/45400/
https://umpir.ump.edu.my/id/eprint/45400/