Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes
Fuzzy Logic Controller (FLC) as speed controller is preferred in many AC machine drives, due to its ability to handle model non-linearity, speed variations and parameters change. Additionally, Self-Tuning FLC (ST-FLC) is a modified FLC controller to overcome the issues associated with a fixed parame...
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Institute of Electrical and Electronics Engineers Inc.
2021
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Online Access: | http://eprints.utem.edu.my/id/eprint/25889/2/INVESTIGATION_OF_THE_COMPUTATIONAL_BURDEN%20%281%29.PDF http://eprints.utem.edu.my/id/eprint/25889/ https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9615218 |
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my.utem.eprints.258892022-04-18T09:59:03Z http://eprints.utem.edu.my/id/eprint/25889/ Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes Yahya Farah, Nabil Salem Talib, Md Hairul Nizam Ibrahim, Zulkifilie Azri, Maaspaliza Mat Lazi, Jurifa Abdullah, Qazwan Aydoğdu, Ömer Mat Isa, Zainuddin Fuzzy Logic Controller (FLC) as speed controller is preferred in many AC machine drives, due to its ability to handle model non-linearity, speed variations and parameters change. Additionally, Self-Tuning FLC (ST-FLC) is a modified FLC controller to overcome the issues associated with a fixed parameter FLC and to avoid performance degradation of the machine drive. It can update the FLC parameters in accordance to any variation, changes or disturbances that may occur to the drive system. However, FLC system requires huge computation capacity which increases the computational burden of the overall machine drive system and may result in poor performance. This research proposed a simple ST-FLC mechanism to tune the main FLC speed controller. Three different rule-size of FLC (9, 25, and 49) rules are implemented with ST-FLC mechanism based Induction Motor (IM) drive. Performance comparison of the three different rule-size based ST-FLC is conducted based on simulation and experimental analysis. In addition, a computational effort is technically analyzed and compared for the three different rule-size. In the experiment, ST-FLC with less number of rules (9-rules) shows superior performance, lower sampling and lower computational efforts compared to ST-FLC with higher rule-size (25, 49) rules. Institute of Electrical and Electronics Engineers Inc. 2021-11 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25889/2/INVESTIGATION_OF_THE_COMPUTATIONAL_BURDEN%20%281%29.PDF Yahya Farah, Nabil Salem and Talib, Md Hairul Nizam and Ibrahim, Zulkifilie and Azri, Maaspaliza and Mat Lazi, Jurifa and Abdullah, Qazwan and Aydoğdu, Ömer and Mat Isa, Zainuddin (2021) Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes. IEEE Access, 9. pp. 155443-155456. ISSN 2169-3536 https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9615218 10.1109/ACCESS.2021.3128351 |
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Fuzzy Logic Controller (FLC) as speed controller is preferred in many AC machine drives, due to its ability to handle model non-linearity, speed variations and parameters change. Additionally, Self-Tuning FLC (ST-FLC) is a modified FLC controller to overcome the issues associated with a fixed parameter FLC and to avoid performance degradation of the machine drive. It can update the FLC parameters in accordance to any variation, changes or disturbances that may occur to the drive system. However, FLC system requires huge computation capacity which increases the computational burden of the overall machine drive system and may result in poor performance. This research proposed a simple ST-FLC mechanism to tune the main FLC speed controller. Three different rule-size of FLC (9, 25, and 49) rules are implemented with ST-FLC mechanism based Induction Motor (IM) drive. Performance comparison of the three different rule-size based ST-FLC is conducted based on simulation and experimental analysis. In addition, a computational effort is technically analyzed and compared for the three different rule-size. In the experiment, ST-FLC with less number of rules (9-rules) shows superior performance, lower sampling and lower computational efforts compared to ST-FLC with higher rule-size (25, 49) rules. |
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Article |
author |
Yahya Farah, Nabil Salem Talib, Md Hairul Nizam Ibrahim, Zulkifilie Azri, Maaspaliza Mat Lazi, Jurifa Abdullah, Qazwan Aydoğdu, Ömer Mat Isa, Zainuddin |
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Yahya Farah, Nabil Salem Talib, Md Hairul Nizam Ibrahim, Zulkifilie Azri, Maaspaliza Mat Lazi, Jurifa Abdullah, Qazwan Aydoğdu, Ömer Mat Isa, Zainuddin Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes |
author_facet |
Yahya Farah, Nabil Salem Talib, Md Hairul Nizam Ibrahim, Zulkifilie Azri, Maaspaliza Mat Lazi, Jurifa Abdullah, Qazwan Aydoğdu, Ömer Mat Isa, Zainuddin |
author_sort |
Yahya Farah, Nabil Salem |
title |
Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes |
title_short |
Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes |
title_full |
Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes |
title_fullStr |
Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes |
title_full_unstemmed |
Investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes |
title_sort |
investigation of the computational burden effects of self-tuning fuzzy logic speed controller of induction motor drives with different rules sizes |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2021 |
url |
http://eprints.utem.edu.my/id/eprint/25889/2/INVESTIGATION_OF_THE_COMPUTATIONAL_BURDEN%20%281%29.PDF http://eprints.utem.edu.my/id/eprint/25889/ https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9615218 |
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1731229673814228992 |
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13.160551 |