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Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization
This paper presents an interval type-2 fuzzy proportional–integral–derivative (IT2F-PID) controller that is designed using a new disassembled gradational optimization (D-GO) method. A PID controller is first optimized using the D-GO method and then connected to a type-1 fuzzy logic system (T1-FLS)....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675177/ https://www.ncbi.nlm.nih.gov/pubmed/38005453 http://dx.doi.org/10.3390/s23229067 |
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author | Chu, Yongzhi Han, Hasiaoqier Ma, Tianjiao Zhu, Mingchao Li, Zhongcan Xu, Zhenbang Wu, Qingwen |
author_facet | Chu, Yongzhi Han, Hasiaoqier Ma, Tianjiao Zhu, Mingchao Li, Zhongcan Xu, Zhenbang Wu, Qingwen |
author_sort | Chu, Yongzhi |
collection | PubMed |
description | This paper presents an interval type-2 fuzzy proportional–integral–derivative (IT2F-PID) controller that is designed using a new disassembled gradational optimization (D-GO) method. A PID controller is first optimized using the D-GO method and then connected to a type-1 fuzzy logic system (T1-FLS). The parameters of the T1-FLS are optimized, and the T1-FLS is blurred into the interval type-2 fuzzy logic system (IT2-FLS). Finally, the IT2F-PID controller is formed. The proposed method is compared with the concurrent and general optimization methods. The simulation results show that the D-GO method reduces the optimization time by over 90% compared with the general method, and decreases the integral-of-time-absolute-error (ITAE) by 30%. Beyond that, compared with the concurrent optimization method, the D-GO method reduces time by over 25%, and the ITAE value by about 95%. In the normal case, model uncertainty, target uncertainty, and external disturbance, the control ability of the IT2F-PID controller designed using the D-GO method is verified via simulations using a nonlinear forced closed-loop system. The results show that the overshoot is reduced by 80% and the fluctuation is reduced by 67% compared with a traditional PID controller and an IT2F-PID controller built using the general method. |
format | Online Article Text |
id | pubmed-10675177 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106751772023-11-09 Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization Chu, Yongzhi Han, Hasiaoqier Ma, Tianjiao Zhu, Mingchao Li, Zhongcan Xu, Zhenbang Wu, Qingwen Sensors (Basel) Article This paper presents an interval type-2 fuzzy proportional–integral–derivative (IT2F-PID) controller that is designed using a new disassembled gradational optimization (D-GO) method. A PID controller is first optimized using the D-GO method and then connected to a type-1 fuzzy logic system (T1-FLS). The parameters of the T1-FLS are optimized, and the T1-FLS is blurred into the interval type-2 fuzzy logic system (IT2-FLS). Finally, the IT2F-PID controller is formed. The proposed method is compared with the concurrent and general optimization methods. The simulation results show that the D-GO method reduces the optimization time by over 90% compared with the general method, and decreases the integral-of-time-absolute-error (ITAE) by 30%. Beyond that, compared with the concurrent optimization method, the D-GO method reduces time by over 25%, and the ITAE value by about 95%. In the normal case, model uncertainty, target uncertainty, and external disturbance, the control ability of the IT2F-PID controller designed using the D-GO method is verified via simulations using a nonlinear forced closed-loop system. The results show that the overshoot is reduced by 80% and the fluctuation is reduced by 67% compared with a traditional PID controller and an IT2F-PID controller built using the general method. MDPI 2023-11-09 /pmc/articles/PMC10675177/ /pubmed/38005453 http://dx.doi.org/10.3390/s23229067 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chu, Yongzhi Han, Hasiaoqier Ma, Tianjiao Zhu, Mingchao Li, Zhongcan Xu, Zhenbang Wu, Qingwen Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization |
title | Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization |
title_full | Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization |
title_fullStr | Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization |
title_full_unstemmed | Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization |
title_short | Interval Type-2 Fuzzy PID Controller Using Disassembled Gradational Optimization |
title_sort | interval type-2 fuzzy pid controller using disassembled gradational optimization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675177/ https://www.ncbi.nlm.nih.gov/pubmed/38005453 http://dx.doi.org/10.3390/s23229067 |
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