Comparative Performance Evaluation of Fractional Fuzzy Inference System for A High-Order System

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dc.authorscopusid25921891300
dc.authorscopusid56108025700
dc.authorscopusid6602646593
dc.contributor.authorCengiz M.
dc.contributor.authorDeniz F.N.
dc.contributor.authorOzguven O.
dc.date.accessioned2024-08-04T20:03:59Z
dc.date.available2024-08-04T20:03:59Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023 -- 23 November 2023 through 25 November 2023 -- 196776en_US
dc.description.abstractIn this study, the effect of the Fractional Fuzzy Inference System (FFIS) on the performance of the fuzzy logic-based control system was examined, with comparisons made to both a typical fuzzy controller and a PID controller. Additionally, a Genetic Algorithm (GA) was utilized to fine-tune the universe of input and output variables for the Fuzzy Logic Controller (FLC) built with FFIS. A high-order system, in which control with classical methods is considered difficult, was chosen to be employed for the performance evaluation. As a result, it has been observed that the use of FFIS in controlling the high-order system leads to a more satisfactory control performance. This study demonstrates that FFIS has the capacity to enhance performance in fuzzy logic-based control systems and can serve as a more effective control strategy. © 2023 IEEE.en_US
dc.identifier.doi10.1109/ISAS60782.2023.10391480
dc.identifier.isbn9798350383065
dc.identifier.scopus2-s2.0-85184824664en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISAS60782.2023.10391480
dc.identifier.urihttps://hdl.handle.net/11616/92248
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofISAS 2023 - 7th International Symposium on Innovative Approaches in Smart Technologies, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectfractional fuzzy inference systemen_US
dc.subjectfuzzy logic controlleren_US
dc.subjectgenetic algorithmen_US
dc.titleComparative Performance Evaluation of Fractional Fuzzy Inference System for A High-Order Systemen_US
dc.typeConference Objecten_US

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