Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System
Controlling the flowrate ratio of two streams in chemical processes poses a challenge due to complex interaction between streams, resulting in nonlinear behaviour and uncertain dynamics. Conventional linear control methods might not be effective to maintain the desired ratio under varying conditions...
Published in: | 2024 IEEE 15TH CONTROL AND SYSTEM GRADUATE RESEARCH COLLOQUIUM, ICSGRC 2024 |
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Main Authors: | , , , , , |
Format: | Proceedings Paper |
Language: | English |
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IEEE
2024
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Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001345150000025 |
author |
Abdullah Nurul Fazlika Syahira; Abdullah Zalizawati; Kasmuri Nor Hazelah; Subari Fuzieah; Hanipah Suhaiza Hanim |
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Abdullah Nurul Fazlika Syahira; Abdullah Zalizawati; Kasmuri Nor Hazelah; Subari Fuzieah; Hanipah Suhaiza Hanim Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System Automation & Control Systems; Engineering |
author_facet |
Abdullah Nurul Fazlika Syahira; Abdullah Zalizawati; Kasmuri Nor Hazelah; Subari Fuzieah; Hanipah Suhaiza Hanim |
author_sort |
Abdullah |
spelling |
Abdullah, Nurul Fazlika Syahira; Abdullah, Zalizawati; Kasmuri, Nor Hazelah; Subari, Fuzieah; Hanipah, Suhaiza Hanim Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System 2024 IEEE 15TH CONTROL AND SYSTEM GRADUATE RESEARCH COLLOQUIUM, ICSGRC 2024 English Proceedings Paper Controlling the flowrate ratio of two streams in chemical processes poses a challenge due to complex interaction between streams, resulting in nonlinear behaviour and uncertain dynamics. Conventional linear control methods might not be effective to maintain the desired ratio under varying conditions. This study evaluates the efficacy of fuzzy logic controller in controlling the flow ratio of model plant WF922. A comparative analysis is conducted with a conventional proportional integral (PI) controller, assessing their performance using integral time-weighted absolute error (ITAE) and integral absolute error (IAE) as key performance indicators. Optimal control settings were determined as PB=0.047 % and I=0.512 s for PI controller, and e=1 % and Delta e=1 % for fuzzy logic controller. The study reveals that fuzzy logic controller showed better performance than PI controller in terms of set point tracking, with reduced overshoot, faster response, and setting times. The fuzzy logic controller outperformed the PI controller across a wider range of set point values, achieving ITAE values lower than 81 and IAE values lower than 4.2. Furthermore, fuzzy logic controller demonstrated quicker and damped responses for disturbance rejection, resulting in lower ITAE and IAE values across all disturbance magnitudes. The findings of this study highlight the potential advantages of employing fuzzy logic controller strategies in liquid flow systems, offering superior set point tracking and disturbance rejection performance compared to conventional PI controller. The findings are useful for improving control system design in industrial applications. IEEE 2638-1710 2024 10.1109/ICSGRC62081.2024.10691107 Automation & Control Systems; Engineering WOS:001345150000025 https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001345150000025 |
title |
Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System |
title_short |
Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System |
title_full |
Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System |
title_fullStr |
Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System |
title_full_unstemmed |
Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System |
title_sort |
Comparative Assessment of Fuzzy Logic and PI Controllers for Ratio Control in Liquid Flow System |
container_title |
2024 IEEE 15TH CONTROL AND SYSTEM GRADUATE RESEARCH COLLOQUIUM, ICSGRC 2024 |
language |
English |
format |
Proceedings Paper |
description |
Controlling the flowrate ratio of two streams in chemical processes poses a challenge due to complex interaction between streams, resulting in nonlinear behaviour and uncertain dynamics. Conventional linear control methods might not be effective to maintain the desired ratio under varying conditions. This study evaluates the efficacy of fuzzy logic controller in controlling the flow ratio of model plant WF922. A comparative analysis is conducted with a conventional proportional integral (PI) controller, assessing their performance using integral time-weighted absolute error (ITAE) and integral absolute error (IAE) as key performance indicators. Optimal control settings were determined as PB=0.047 % and I=0.512 s for PI controller, and e=1 % and Delta e=1 % for fuzzy logic controller. The study reveals that fuzzy logic controller showed better performance than PI controller in terms of set point tracking, with reduced overshoot, faster response, and setting times. The fuzzy logic controller outperformed the PI controller across a wider range of set point values, achieving ITAE values lower than 81 and IAE values lower than 4.2. Furthermore, fuzzy logic controller demonstrated quicker and damped responses for disturbance rejection, resulting in lower ITAE and IAE values across all disturbance magnitudes. The findings of this study highlight the potential advantages of employing fuzzy logic controller strategies in liquid flow systems, offering superior set point tracking and disturbance rejection performance compared to conventional PI controller. The findings are useful for improving control system design in industrial applications. |
publisher |
IEEE |
issn |
2638-1710 |
publishDate |
2024 |
container_volume |
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container_issue |
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doi_str_mv |
10.1109/ICSGRC62081.2024.10691107 |
topic |
Automation & Control Systems; Engineering |
topic_facet |
Automation & Control Systems; Engineering |
accesstype |
|
id |
WOS:001345150000025 |
url |
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001345150000025 |
record_format |
wos |
collection |
Web of Science (WoS) |
_version_ |
1823296085477556224 |