Review and Investigation of Simplified Rules Fuzzy Logic Speed Controller of High Performance Induction Motor Drives

dc.contributor.author Tarbosh, Qazwan A.
dc.contributor.author Aydoğdu, Ömer
dc.contributor.author Farah, Nabil
dc.contributor.author Talib, Hairul Nizam
dc.contributor.author Salh, Adeeb
dc.contributor.author Cankaya, Nihat
dc.contributor.author Durdu, Akif
dc.date.accessioned 2021-12-13T10:38:45Z
dc.date.available 2021-12-13T10:38:45Z
dc.date.issued 2020
dc.description.abstract The use of Fuzzy Logic Controller (FLC) as a speed controller for Induction Motor (IM) drives is garnering strong researchers' interest since it has proven to achieve superior performance compared to conventional controllers. The aim of this study is to review and investigate the design, operations, and effects of rules reduction for FLC in IM drives. Based on the literature, the most commonly used technique to design FLC Membership Functions (MFs) rule-base and control model is based on engineering skills and experienced behavioral aspects of the controlled system. Simplified fuzzy rules approaches have been introduced to reduce the number of fuzzy rules in order to realize hardware implementation. This study discusses different simplified rules methods applied to IM drives. Most of the proposed methods shared a common drawback in that they lacked systematic procedures for designing FLC rule base. Therefore, this research proposed a methodological approach to designing and simplifying the FLC rule-base for IM drives based on dynamic step response and phase plane trajectory of the second order representation of IM drives systems. The proposed method presents guidance for designing FLC rule-base based on the general dynamic step response of the controlled system. Following the proposed method procedures, a (9, 25, 49) rules size has been designed and simplified to a (5, 7, 9) rules size. The effectiveness and accuracy of the designed rules as well as the simplified rules were verified by conducting simulation analysis of IM drives using MATLAB/Simulink environment. Step speed command performance comparisons were achieved with both standard designed and simplified rules at various speed demands. The simulation results showed that the simplified rules maintain the drive performance and produced similar behavior as the standard designed rules. en_US
dc.identifier.doi 10.1109/ACCESS.2020.2977115
dc.identifier.issn 2169-3536
dc.identifier.scopus 2-s2.0-85082391558
dc.identifier.uri https://doi.org/10.1109/ACCESS.2020.2977115
dc.identifier.uri https://hdl.handle.net/20.500.13091/1339
dc.language.iso en en_US
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC en_US
dc.relation.ispartof IEEE ACCESS en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Fuzzy Logic en_US
dc.subject Fuzzy Sets en_US
dc.subject Mathematical Model en_US
dc.subject Control Systems en_US
dc.subject Rotors en_US
dc.subject Stators en_US
dc.subject Hardware en_US
dc.subject Flc en_US
dc.subject Im Drives en_US
dc.subject Simplified Rules en_US
dc.subject Rule-Base en_US
dc.subject Step Response en_US
dc.subject Phase-Plane en_US
dc.subject Systematic en_US
dc.subject Field-Oriented Control en_US
dc.subject Direct Torque Control en_US
dc.subject Indirect Vector Control en_US
dc.subject Control-Systems en_US
dc.subject Pi Controllers en_US
dc.subject Reduction en_US
dc.subject Optimization en_US
dc.subject Interval en_US
dc.subject Design en_US
dc.subject Identification en_US
dc.title Review and Investigation of Simplified Rules Fuzzy Logic Speed Controller of High Performance Induction Motor Drives en_US
dc.type Review en_US
dspace.entity.type Publication
gdc.author.id TARBOSH, QAZWAN ABDULLAH/0000-0003-0623-2286
gdc.author.scopusid 57215928415
gdc.author.scopusid 14833966800
gdc.author.scopusid 57192554546
gdc.author.scopusid 54891405600
gdc.author.scopusid 57193130837
gdc.author.scopusid 57208479578
gdc.author.scopusid 57215930278
gdc.author.wosid TARBOSH, QAZWAN ABDULLAH/AAQ-5084-2020
gdc.author.wosid Durdu, Akif/AAQ-4344-2020
gdc.author.wosid Salh, Adeb/AAP-8018-2021
gdc.author.wosid OMAR, Fuad ALHAJ/AAX-1447-2021
gdc.author.wosid Cankaya, Nihat/R-9039-2019
gdc.author.wosid Farah, Nabil Salem/P-5154-2018
gdc.author.wosid Farah, Nabil/O-9207-2019
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gdc.coar.access open access
gdc.coar.type text::review
gdc.description.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü en_US
gdc.description.endpage 49394 en_US
gdc.description.publicationcategory Diğer en_US
gdc.description.scopusquality Q1
gdc.description.startpage 49377 en_US
gdc.description.volume 8 en_US
gdc.description.wosquality Q2
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gdc.oaire.keywords Artificial intelligence
gdc.oaire.keywords Astronomy
gdc.oaire.keywords FOS: Political science
gdc.oaire.keywords Trajectory
gdc.oaire.keywords Adaptive Control
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gdc.oaire.keywords Induction motor
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gdc.oaire.keywords Analysis of Electric Machinery and Drive Systems
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gdc.oaire.keywords rule-base
gdc.oaire.keywords Controller (irrigation)
gdc.oaire.keywords Voltage
gdc.oaire.keywords Fuzzy rule
gdc.oaire.keywords Neural Network Fundamentals and Applications
gdc.oaire.keywords Computer science
gdc.oaire.keywords Agronomy
gdc.oaire.keywords TK1-9971
gdc.oaire.keywords Fuzzy logic
gdc.oaire.keywords Operating system
gdc.oaire.keywords Fuzzy control system
gdc.oaire.keywords Electrical engineering
gdc.oaire.keywords Computer Science
gdc.oaire.keywords simplified rules
gdc.oaire.keywords Representation (politics)
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gdc.opencitations.count 46
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gdc.scopus.citedcount 66
gdc.virtual.author Aydoğdu, Ömer
gdc.virtual.author Durdu, Akif
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