6. FUZZY INFERENCES IFK15037, 3 credits · Rinaldi Munir STEI ITB 7 FuzzyficaPon Fuzzy Logic...
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Transcript of 6. FUZZY INFERENCES IFK15037, 3 credits · Rinaldi Munir STEI ITB 7 FuzzyficaPon Fuzzy Logic...
HISTORY
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ProfessorLoKiA.Zadeh
In1965,Lo,iA.ZadehoftheUniversityofCaliforniaatBerkeleypublished"FuzzySets,"whichlaidoutthemathemaJcsoffuzzysettheoryand,byextension,fuzzylogic.ZadehhadobservedthatconvenJonalcomputerlogiccouldnotmanipulatedatathatrepresentedsubjecJveorvagueideas,sohecreatedfuzzylogictoallowcomputerstodeterminethedisJncJonsamongdatawithshadesofgray,similartotheprocessofhumanreasoning.hNp://www.cs.berkeley.edu/~zadeh/
ExampleofApplicaPons
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• InthecityofSendaiinJapan,a16-staJonsubwaysystemiscontrolledbyafuzzycomputer(SeijiYasunobuandSojiMiyamotoofHitachi)–therideissosmooth,ridersdonotneedtoholdstraps
• Nissan–fuzzyautomaJctransmission,fuzzyanJ-skidbrakingsystem• CSK,Hitachi–Hand-wriJngRecogniJon• Sony-Hand-printedcharacterrecogniJon• Ricoh,Hitachi–VoicerecogniJon• Tokyo’sstockmarkethashadatleastonestock-tradingporKoliobasedon
FuzzyLogicthatoutperformedtheNikkeiexchangeaverage• NASAhasstudiedfuzzycontrolforautomatedspacedocking:simulaJons
showthatafuzzycontrolsystemcangreatlyreducefuelconsumpJon• Canondevelopedanauto-focusingcamerathatusesacharge-coupled
device(CCD)tomeasuretheclarityoftheimageinsixregionsofitsfieldofviewandusetheinformaJonprovidedtodetermineiftheimageisinfocus.Italsotrackstherateofchangeoflensmovementduringfocusing,andcontrolsitsspeedtopreventovershoot.
IntroducPonofFIS
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● AFuzzyInferenceSystem(FIS)isawayofmappinganinputspacetoanoutputspaceusingfuzzylogic
● FIS uses a collecJon of fuzzy membership funcJonsandrules,insteadofBooleanlogic.
● The rules in FIS (someJmes may be called as fuzzyexpertsystem)arefuzzyproducJonrulesoftheform:− ifpthenq,wherepandqarefuzzystatements.
● Forexample,inafuzzyrule− ifxislowandyishighthenzismedium.− Here x is low; y is high; z is medium are fuzzystatements;xandyareinputvariables;zisanoutputvariable,low,high,andmediumarefuzzysets.
IntroducPonofFIS(cont.)
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● The antecedent describes towhat degree the ruleapplies, while the conclusion assigns a fuzzyfuncJontoeachofoneormoreoutputvariables.● Most tools for working with fuzzy expert systemsallowmorethanoneconclusionperrule.● Thesetofrulesinafuzzyexpertsystemisknownasknowledgebase.
StructureofFuzzyExpertSystems
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KnowledgeBase
InferenceEngine
FuzzificaPon
DefuzzficaPon
Crispvalue
Crispvalue
FuncPonalProcess
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FuzzyficaPon
FuzzyLogicOperaPon
ImplicaPon
AgregaPon
DefuzzyficaPon
INPUT
OUTPUT
CrispvalueàfuzzymembershipfuncJon
AntecedentmaybejoinedbyOR;ANDoperators
FuzzyficaPon
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Fuzzyfikasi:prosesmemetakannilaicrisp(numerik)kedalamhimpunanfuzzydanmenentukanderajatkeanggotaannyadidalamhimpunanfuzzy.Halinidilakukankarenadatadiprosesberdasarkanteorihimpunanfuzzysehinggadatayangbukandalambentukfuzzyharusdiubahkedalambentukfuzzy.
Example:FuzzyficaPon
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Example:FuzzyficaPon
Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy10
FuzzyMembershipFuncPon
FuzzyLogicwithEngineeringApplicaJons:TimothyJ.Ross11
TypesofMembershipFuncJons•ThemostcommonlyusedinpracJceare–Triangles–Trapezoids–Bellcurves–Gaussian,and–Sigmoidal
FuzzyMembershipFuncPon
FuzzyLogicwithEngineeringApplicaJons:TimothyJ.Ross12
FuzzyMembershipFuncPon
FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall13
FuzzyMembershipFuncPon
FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall14
FuzzyMembershipFuncPon
FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall15
FuzzyMembershipFuncPon
FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall16
FuzzyMembershipFuncPon
FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall17
FuzzyMembershipFuncPon
FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall18
FuzzyLogicOperaPon
Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy19
Jikabagianantesendendihubungkanolehkonektorand,or,dannot,makaderajatkebenarannyadihitungdenganoperasifuzzyyangbersesuaian
ImplicaPon
Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy20
ImplicaPon
Wikipedia21
ImplicaPon
Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy22
AggregaPon
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AggregaPon
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AggregaPon
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AggregaPon
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AggregaPon
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AggregaPon
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AggregaPon
Mathworks29
DefuzzyficaPon
Mathworks30
DefuzzyficaPon
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• Strategiyangumumdipakaidalamdefuzzifikasiadalahmenentukanbentukkompromiterbaik.
• Metode-metodeuntukstrategiiniadalah:1. Metodekeanggotaanmaximum(max-membership)2. Metodepusatluas(CenterofArea,CoA).3. Metodekeanggotaanmaksimumrata-rata(Mean-max
MembershipatauMiddle-of-Maxima)
DefuzzyficaPon
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DefuzzyficaPon
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DefuzzyficaPon
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Thank
