Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system
In order to reduce vibration and increase ride comfort, this article utilizes a system of quarter-car suspension integrated with a Fuzzy PID controller. To build and improve the Fuzzy PID controller for the semi-active suspension system used in quarter cars, using a novel meta-heuristic technique kn...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publications Inc.
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/115677/ http://psasir.upm.edu.my/id/eprint/115677/1/115677.pdf |
| _version_ | 1848866838787653632 |
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| author | Liu, Yunyun As’arry, Azizan Ahmed, Hesham Hairuddin, Abdul Aziz Hassan, Mohd Khair Zakaria, Mohd Zakimi Yang, Shuai |
| author_facet | Liu, Yunyun As’arry, Azizan Ahmed, Hesham Hairuddin, Abdul Aziz Hassan, Mohd Khair Zakaria, Mohd Zakimi Yang, Shuai |
| author_sort | Liu, Yunyun |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In order to reduce vibration and increase ride comfort, this article utilizes a system of quarter-car suspension integrated with a Fuzzy PID controller. To build and improve the Fuzzy PID controller for the semi-active suspension system used in quarter cars, using a novel meta-heuristic technique known as Grey Wolf Optimizer (GWO). Here the magnetorheological damper (MR) fluid with the Fuzzy PID controller was examined to optimize using the GWO algorithm. With the GWO technique and the integral of time absolute error (IAE) as a fitness function, the three gain parameters of the Fuzzy PID controller – Kp, Ki, and Kd– have been optimally set. The suggested approach has additional advantages for the optimization of functions with three variables, including simplicity in implementation, quick convergence traits, and superior computational capabilities. This work is significant, to the best of the author’s knowledge there is no optimization method using GWO to online tune a Fuzzy PID controller for a semi-active suspension system. The optimal output parameters of the controller can be updated online in real-time by GWO. The performance of the proposed controller was examined by assessing the root mean square (RMS) values and peak-to-peak (PTP) values of body displacement and body acceleration under various road profiles. To ensure that the intelligent controller was of the highest caliber, an online test rig was constructed. Results from simulations and online experiments demonstrated that the Fuzzy GWO PID controller significantly improved ride comfort under a variety of road conditions when compared to the Fuzzy PID controller and passive suspension system. |
| first_indexed | 2025-11-15T14:26:58Z |
| format | Article |
| id | upm-115677 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:26:58Z |
| publishDate | 2024 |
| publisher | SAGE Publications Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1156772025-03-10T04:11:22Z http://psasir.upm.edu.my/id/eprint/115677/ Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system Liu, Yunyun As’arry, Azizan Ahmed, Hesham Hairuddin, Abdul Aziz Hassan, Mohd Khair Zakaria, Mohd Zakimi Yang, Shuai In order to reduce vibration and increase ride comfort, this article utilizes a system of quarter-car suspension integrated with a Fuzzy PID controller. To build and improve the Fuzzy PID controller for the semi-active suspension system used in quarter cars, using a novel meta-heuristic technique known as Grey Wolf Optimizer (GWO). Here the magnetorheological damper (MR) fluid with the Fuzzy PID controller was examined to optimize using the GWO algorithm. With the GWO technique and the integral of time absolute error (IAE) as a fitness function, the three gain parameters of the Fuzzy PID controller – Kp, Ki, and Kd– have been optimally set. The suggested approach has additional advantages for the optimization of functions with three variables, including simplicity in implementation, quick convergence traits, and superior computational capabilities. This work is significant, to the best of the author’s knowledge there is no optimization method using GWO to online tune a Fuzzy PID controller for a semi-active suspension system. The optimal output parameters of the controller can be updated online in real-time by GWO. The performance of the proposed controller was examined by assessing the root mean square (RMS) values and peak-to-peak (PTP) values of body displacement and body acceleration under various road profiles. To ensure that the intelligent controller was of the highest caliber, an online test rig was constructed. Results from simulations and online experiments demonstrated that the Fuzzy GWO PID controller significantly improved ride comfort under a variety of road conditions when compared to the Fuzzy PID controller and passive suspension system. SAGE Publications Inc. 2024-02-23 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/115677/1/115677.pdf Liu, Yunyun and As’arry, Azizan and Ahmed, Hesham and Hairuddin, Abdul Aziz and Hassan, Mohd Khair and Zakaria, Mohd Zakimi and Yang, Shuai (2024) Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system. Advances in Mechanical Engineering, 16 (2). pp. 1-14. ISSN 1687-8132; eISSN: 1687-8140 https://journals.sagepub.com/doi/10.1177/16878132231219620 10.1177/16878132231219620 |
| spellingShingle | Liu, Yunyun As’arry, Azizan Ahmed, Hesham Hairuddin, Abdul Aziz Hassan, Mohd Khair Zakaria, Mohd Zakimi Yang, Shuai Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system |
| title | Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system |
| title_full | Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system |
| title_fullStr | Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system |
| title_full_unstemmed | Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system |
| title_short | Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system |
| title_sort | online optimal tuning of fuzzy pid controller using grey wolf optimizer for quarter car semi-active suspension system |
| url | http://psasir.upm.edu.my/id/eprint/115677/ http://psasir.upm.edu.my/id/eprint/115677/ http://psasir.upm.edu.my/id/eprint/115677/ http://psasir.upm.edu.my/id/eprint/115677/1/115677.pdf |