Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules
The paper proposes a methodology to online self-evolve direct fuzzy logic controllers (FLCs), to deal with unknown and time-varying dynamics. The proposed methodology self-designs the controller, where fuzzy control rules can be added or removed considering a predefined criterion. The proposed metho...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/17/5836 |
| _version_ | 1797556102147080192 |
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| author | Jérôme Mendes Ricardo Maia Rui Araújo Francisco A. A. Souza |
| author_facet | Jérôme Mendes Ricardo Maia Rui Araújo Francisco A. A. Souza |
| author_sort | Jérôme Mendes |
| collection | DOAJ |
| description | The paper proposes a methodology to online self-evolve direct fuzzy logic controllers (FLCs), to deal with unknown and time-varying dynamics. The proposed methodology self-designs the controller, where fuzzy control rules can be added or removed considering a predefined criterion. The proposed methodology aims to reach a control structure easily interpretable by human operators. The FLC is defined by univariate fuzzy control rules, where each input variable is represented by a set of fuzzy control rules, improving the interpretability ability of the learned controller. The proposed self-evolving methodology, when the process is under control (online stage), adds fuzzy control rules on the current FLC using a criterion based on the incremental estimated control error obtained using the system’s inverse function and deletes fuzzy control rules using a criterion that defines “less active” and “less informative” control rules. From the results on a nonlinear continuously stirred tank reactor (CSTR) plant, the proposed methodology shows the capability to online self-design the FLC by adding and removing fuzzy control rules in order to successfully control the CSTR plant. |
| first_indexed | 2024-03-10T16:58:06Z |
| format | Article |
| id | doaj.art-8388163bbc6d46b487078a3bb27b1b32 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T16:58:06Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-8388163bbc6d46b487078a3bb27b1b322023-11-20T11:05:15ZengMDPI AGApplied Sciences2076-34172020-08-011017583610.3390/app10175836Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control RulesJérôme Mendes0Ricardo Maia1Rui Araújo2Francisco A. A. Souza3University of Coimbra, Institute of Systems and Robotics, Department of Electrical and Computer Engineering, Pólo II, PT-3030-290 Coimbra, PortugalUniversity of Coimbra, Institute of Systems and Robotics, Department of Electrical and Computer Engineering, Pólo II, PT-3030-290 Coimbra, PortugalUniversity of Coimbra, Institute of Systems and Robotics, Department of Electrical and Computer Engineering, Pólo II, PT-3030-290 Coimbra, PortugalOncontrol Technologies, Lda, Av. Sá Bandeira, 33, Escritório 519, PT-3000-279 Coimbra, PortugalThe paper proposes a methodology to online self-evolve direct fuzzy logic controllers (FLCs), to deal with unknown and time-varying dynamics. The proposed methodology self-designs the controller, where fuzzy control rules can be added or removed considering a predefined criterion. The proposed methodology aims to reach a control structure easily interpretable by human operators. The FLC is defined by univariate fuzzy control rules, where each input variable is represented by a set of fuzzy control rules, improving the interpretability ability of the learned controller. The proposed self-evolving methodology, when the process is under control (online stage), adds fuzzy control rules on the current FLC using a criterion based on the incremental estimated control error obtained using the system’s inverse function and deletes fuzzy control rules using a criterion that defines “less active” and “less informative” control rules. From the results on a nonlinear continuously stirred tank reactor (CSTR) plant, the proposed methodology shows the capability to online self-design the FLC by adding and removing fuzzy control rules in order to successfully control the CSTR plant.https://www.mdpi.com/2076-3417/10/17/5836evolving designfuzzy controllerunivariate fuzzy rulesCSTR plant |
| spellingShingle | Jérôme Mendes Ricardo Maia Rui Araújo Francisco A. A. Souza Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules Applied Sciences evolving design fuzzy controller univariate fuzzy rules CSTR plant |
| title | Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules |
| title_full | Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules |
| title_fullStr | Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules |
| title_full_unstemmed | Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules |
| title_short | Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules |
| title_sort | self evolving fuzzy controller composed of univariate fuzzy control rules |
| topic | evolving design fuzzy controller univariate fuzzy rules CSTR plant |
| url | https://www.mdpi.com/2076-3417/10/17/5836 |
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