反应釜温度智能控制系统设计 2.docx

反应釜温度智能控制系统设计 2.docx

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反应釜温度智能控制系统设计2

Gain-schedulingfuzzytemperaturecontrollerforone-wayinputsystem

Abstract：

Inmanychemicalandsemiconductormanufacturingprocesses,temperatureisanimportantcontrolparameterforobtainingthedesiredproductquality.Generally,thetemperaturecontrolsystemhasnon-lineartime-varying,slowresponse,time-delayandone-waycontrolinputcharacteristics.Itisdifficulttoestimateaccuratelythedynamicmodelanddesignageneral-purposetemperaturecontrollertoachievegoodcontrolperformance.Hereamodel-freeintelligentgain-schedulingfuzzycontrolstrategyisproposedtodesignatemperaturecontrollerforanironclosedchamberwithheaterinputonly.Theconceptofgainschedulingisemployedtoadjustthemappingrangesoffuzzymembershipfunctionsduringthecontrolprocessforimprovingthecontrolperformance.Theexperimentalresultsshowthatthesteady-stateerrorsofthestepinputresponsesarealwayslessthan0.28Cwithoutovershootbyusingthiscontrolscheme.Itissuitableforindustrialtemperaturecontrolsystems

Keyword：

fuzzycontrol,gainscheduling,temperaturecontrolandone-wayinput.

1Introduction

Temperatureisanimportantcontrolparameterinchemical,materialandsemiconductormanufacturingprocesses.Forexample,materialannealing,thinfilmdepositionandTVglassmeltingfurnaceallneedappropriatetemperaturecontrolsystems.Someofthetemperaturecontrolsystemshaveheatingandcoolingcontrolphasesandothersonlyhaveaheatinginputcontrolphase.Theirdynamicbehaviourshavesignificantdifferences.Thetemperaturecontrolsystemwithheaterinputonlyismoredifficulttomonitorthantwophasecontrolsystemstoobtaingoodcontrolperformance.Howtodesignageneral-purposetemperaturecontrollerwithgoodresponsespeed,smallersteady-stateerrorandwithoutovershootforindustrialimplementationisstillachallengeinthecontrolresearchfield.Currently,on–off

controlandPIDcontrolschemesareemployedincommercialproducts.APIDcontrollerwasproposedin1936.Ithasbeenwidelyusedinindustrialautomaticcontrolsystems.However,howtoadjustthecontrolgainsisthekeyfactorofimplementingaPIDcontroller.Iftheaccuratedynamicmodelofacontrolsystemisavailable,theZieglerandNicholsrule（ZieglerandNichols,1942）andIMCcontrolstrategy（ChienandFruehauf,1990;Riveraetal.,1986）canbeusedtocalculatetheappropriategains.However,theheatingplanthastime-delayandtemperaturedependencenon-linearbehaviours.ItishardtoestablishanaccuratedynamicmodelforaPIDcontrollerdesign.Generally,itneedsatrial-and-errorprocesstoobtainagoodcontrolresponse.Whenthesystemhasexternaldisturbanceorset-pointchange,itstransientresponsemaydeteriorate.Itneedsanonlineoperatortoreadjustitorswitchittomanualcontrol.Thisisnotaconvenientapplicationandtheproductionparametersmaynotmaintaininagoodlevelinmanufacturingprocesses.Hencemodel-freeintelligentcontrolschemeshavegainedtheattentionofresearchers.

Aself-tuningPIDcontrolstrategywasproposedtocontrolwaterbathtemperature（Yusofetal.,1994）.Afrequencyloop-shapingtechniqueisemployedtotunethePIDgainsofthetemperaturecontrollerofachemicalvapourdeposition（CVD）diffusionfurnace（GrassiandTsakalis,2000）.Theappropriategainsofthisapproacharesearchedbasedonthesystemoutputresponseofanon–offopen-looprelaycontrol.Inaddition,fuzzycontrolhasbeensuccessfulemployedinmanyindustrialprocesses,asithasmodel-freeintelligentcharacteristics.Recently,fuzzycontroltheoryhasbeenusedtoimprovetheadaptivityandrobustnessofaPIDcontroller.AhybridfuzzyandPIcontrolforTVglassmeltingfurnacetemperaturecontrolhasbeenproposed（MoonandLee,2000,2003）.ThefuzzylogicschemealsoisappliedtoadjustPIDcontrollergains（ChenandLi,2003;Heetal.,1993;Visioli,2001）.ThePIDgainsoftheseapproachesarenon-linearfunctionsoftrackingcontrolperformance.Theycanbeadjustedautomaticallybasedontheoutputerror.Itcanachievebetterrobustness,quickresponseandsmallerovershootthanthatofatraditionalPIDcontroller.However,itisdifficulttodesignageneral-purposefuzzycontrolrulestableandthecorrespondingfuzzyparameters.Hence,aself-organizingfuzzycontroller（LuandChen,1994）andadaptivefuzzycontrolscheme（Haissig,1999）wereemployedtodesignthetemperaturecontrollertoobtainthestableadaptivebehaviour,butthesecontrolstrategiesstillcannotachievebothaquicktransientresponseandanaccuratesteady-stateresponse.

Usually,temperaturecontrolsystemshavenon-lineartime-varyingandtime-delaycharacteristics.Itisdifficulttoestimateanappropriatedynamicmodelformodel-basedcontrollerdesign.Especially,thetemperaturecontrolproblemwithone-wayheaterinputonlyhastime-delayandasymmetriccontrolbehaviour.Itisdifficulttoachieveprecisetemperaturecontrolaccuracywithagoodtransientresponsebasedontraditionalcontrolalgorithms.Herethemodel-freegain-schedulingfuzzycontrolschemeisemployedtodesigntheheaterinputsingle-phasetemperaturecontrollerwithfuzzygainparameters,auto-switchingtoachieveagoodtransientresponseandsmallsteady-stateerror.Ageneral-purposeintelligenttemperaturecontrolleristhedesignedgoalofthispaper.Thetemperaturedynamicresponseperformanceofthefuzzygain-schedulingcontrollerwillbecomparedwiththatofanauto-tuningPIDcontroller.Theexperimentaltestrigisahollowmetalchamberwithheatercontrolinputonly.

2Systemstructure

ThePC-basedcontrolsystemstructureofatemperaturemonitoringsystemisshowninFigure1.ThePCsendsthecontrolvoltageintoanSCRdriverthroughtheD/Acard.A12-bitlowcostASIO-113AD/DA/8255interfacecardisselectedforthiscontrolsystem.TheMAXTHERMOSCRdriverhasa250innerresistancetotransformthe1–5Vcontrolvoltageinto4–20mAcontrolinputcurrentfortheheatingrod.ThisSCRcanmonitorthepoweroutputofasingle-phase110-Vand20-Aalternativecurrentpowersource.Itregulatesthecurrentinputoftheheatingrodforraisingthetemperatureofthehollowmetalchamber.Themediuminsidethehollowcylinderchamberisair.Thetemperatureofthehollowmetalcylinderismeasuredusingaresistancetemperaturesensor（RTD）andfedbackintothePCthroughtheA/Dcard.ThetemperaturecontrolalgorithmisimplementedwithCþþprogram.Ahollowmetalchamberexperimentaltestrigisbuiltforevaluatingthecontrolperformance.Thedimensionofthehollowironcylinderis250mminheightand51mmindiameterwitha10-mmdiameterhollowholeforinstallingtheheatingrodandtheRTDPT100temperaturesensor.TheaccuracyoftheselectedPT100RTSsensorisabout0.28Cwithinthe3008Ctemperaturemeasuringrange.ThesensitivityofthisRTDsensoris0.0015per8C.Thesamplingfrequencyofthefollowingexperimentsissetas40Hz.

3Auto-tuningPIDcontrol

ThekeyfactorswhichinfluencethecontrolsystemperformanceofaPIDcontrollerishowtofindtheoptimalproportionalgain,integraltimeconstantandderivativetimeconstant.Forpracticalimplementation,thesegainsadjustmentsareachievedbyexpertiseoranexperiencedengineer,andatrial-and-errormodification.Itistime-consumingworkandthedynamicresponsebehaviourcannotbeguaranteed.Hence,arelayfeedbackevaluationmethodwasproposedtofindthegainparametersofaPIDcontroller（AstromandHagglund,1984）.Firstly,anon–offswitchingcontrolisemployedforthefirsttwocycles.Whenthesystemtemperatureislessthanthesettingcommand,thecontrolpowerisfullyopenedtodrivethetemperatureup.

Figure1PC-basedtemperaturecontrolsystemstructure

Whenthetemperaturereachesthesettingvalue,thecontrolinputisswitchedoffimmediately.Thenthecriticalgain,Ku,andcriticalperiod,Pu,canbefoundfromtheseinput–outputresponsecurvesasFigure2,where

Hence,thegainparameterscanbecalculatedbyusingtheexperiencedformulaofZiegler–Nichols.

Figure2Theestimatingofcriticalperiodandcriticalgainfromon–offcontrol

4Gain-schedulingfuzzylogiccontroller

Sincethistemperaturecontrolsystemhasobvioustime-delayandone-wayinputnon-linearbehaviour,itisdifficulttoestablishanappropriatedynamicmodelfortheprecisemodel-basedcontrollerdesign.Inaddition,theovershoottransientresponseofthetemperaturecontrolsystem,withtime-delayandsingle-phaseheatinginputdynamicfeatures,isdifficulttoavoidandeliminatequickly.Hence,howtodesignageneral-purposetemperaturecontrollerwithsmallovershootandquickresponsewillbeachallengeresearchtopic.Herethemodel-freegain-schedulingfuzzycontrolstrategyisproposedtosolvethisproblem.ThecontrolblockdiagramisshowninFigure3.

Usuallythemotivationofafuzzyapproachisthattheknowledgeisinsufficientandthedynamicmodelhasuncertainty.Fuzzysettheorywasemployedtosimulatethelogicreasoningofhumanbeings.Themajorcomponentsofafuzzycontrollerareasetoflinguisticfuzzycontrolrulesandaninferenceenginetointerprettheserules.

Figure3Fuzzycontrolblockdiagramofthetemperaturecontrolsystem

Thesefuzzyrulesofferatransformationbetweenthelinguisticcontrolknowledgeofanexpertandtheautomaticcontrolstrategiesofanactivator.Everyfuzzycontrolruleiscomposedofanantecedentandaconsequent;ageneralformoftherulescanbeexpressedas

R:

IFXisAandYsiA,THENUisCI

inputvariableseandce.TheyareNB,NM,NS,ZO,PS,PMandPB.Themembershipfunctionsofthesefuzzyvariablesa