外文翻译Word格式.docx

外文翻译Word格式.docx

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Thevariablefrequencyspeed-regulatingsystemwhichconsistsofaninductionmotorandageneralinverter,andcontrolledbyPLCiswidelyusedinindustrialfield.However,forthemultivariable,nonlinearandstronglycoupledinductionmotor,thecontrolperformanceisnotgoodenoughtomeettheneedsofspeed-regulating.Themathematicmodelofthevariablefrequencyspeed-regulatingsysteminvectorcontrolmodeispresentedanditsreversibilityhasbeenproved.Byconstructinganeuralnetworkinversesystemandcombiningitwiththevariablefrequencyspeed-regulatingsystem,apseudo-linearsystemiscompleted,andthenalinearclose-loopadjustorisdesignedtogethighperformance.UsingPLC,aneuralnetworkinversesystemcanberealizedinacturalsystem.Theresultsofexperimentshaveshownthattheperformancesofvariablefrequencyspeed-regulatingsystemcanbeimprovedgreatlyandthepracticabilityofneuralnetworkinversecontrolwastestified.

1.Citation:

Inrecentyears,withpowerelectronictechnology,microelectronictechnologyandmoderncontroltheoryinfiltratingintoACelectricdrivingsystem,invertershavebeenwidelyusedinspeed-regulatingofACmotor.Thevariablefrequencyspeed-regulatingsystemwhichconsistsofaninductionmotorandageneralinverterisusedtotaketheplaceofDCspeed-regulatingsystem.Becauseofterribleenvironmentandseveredisturbanceinindustrialfield,thechoiceofcontrollerisanimportantproblem.Somereference,Neuralnetworkinversecontrolwasrealizedbyusingindustrialcontrolcomputerandseveraldataacquisitioncards.Theadvantagesofindustrialcontrolcomputerarehighcomputationspeed,greatmemorycapacityandgoodcompatibilitywithothersoftwareetc.Butindustrialcontrolcomputeralsohassomedisadvantagesinindustrialapplicationsuchasinstabilityandfallibilityandworsecommunicationability.PLCcontrolsystemisspecialdesignedforindustrialenvironmentapplication,anditsstabilityandreliabilityaregood.PLCcontrolsystemcanbeeasilyintegratedintofieldbuscontrolsystemwiththehighabilityofcommunicationconfiguration,soitiswildlyusedinrecentyears,anddeeplywelcomed.Sincethesystemcomposedofnormalinverterandinductionmotorisacomplicatednonlinearsystem,traditionalPIDcontrolstrategycouldnotmeettherequirementforfurthercontrol.Therefore,howtoenhancecontrolperformanceofthissystemisveryurgent.

Theneuralnetworkinversesystem,isanovelcontrolmethodinrecentyears.Thebasicideaisthat:

foragivensystem,aninversesystemoftheoriginalsystemiscreatedbyadynamicneuralnetwork,andthecombinationsystemofinverseandobjectistransformedintoakindofdecouplingstandardizedsystemwithlinearrelationship.Subsequently,alinearclose-loopregulatorcanbedesignedtoachievehighcontrolperformance.Theadvantageofthismethodiseasilytoberealizedinengineering.Thelinearizationanddecouplingcontrolofnormalnonlinearsystemcanrealizeusingthismethod.

CombiningtheneuralnetworkinverseintoPLCcaneasilymakeuptheinsufficiencyofsolvingtheproblemsofnonlinearandcouplinginPLCcontrolsystem.Thiscombinationcanpromotetheapplicationofneuralnetworkintopracticetoachieveitfulleconomicandsocialbenefits.

Inthispaper,firstlytheneuralnetworkinversesystemmethodisintroduced,andmathematicmodelofthevariablefrequencyspeed-regulatingsysteminvectorcontrolmodeispresented.Thenareversibleanalysisofthesystemisperformed,andthemethodsandstepsaregiveninconstructingNN-inversesystemwithPLCcontrolsystem.Finally,themethodisverifiedinexperiments,andcomparedwithtraditionalPIcontrolandNN-inversecontrol.

2.NeuralNetworkInverseSystemControlMethod

Thebasicideaofinversecontrolmethodisthat:

foragivensystem,anα-thintegralinversesystemoftheoriginalsystemiscreatedbyfeedbackmethod,andcombiningtheinversesystemwithoriginalsystem,akindofdecouplingstandardizedsystemwithlinearrelationshipisobtained,whichisnamedasapseudolinearsystem.Subsequently,alinearclose-loopregulatorwillbedesignedtoachievehighcontrolmathematicmodelofthevariableperformance.

Inversesystemcontrolmethodwiththefeaturesofdirect,simpleandeasytounderstanddoesnotlikedifferentialgeometrymethod,whichisdiscussestheproblemsin"

geometrydomain"

.Themainproblemistheacquisitionoftheinversemodelintheapplications.Sincenon-linearsystemisacomplexsystem,anddesiredstrictanalyticalinverseisveryobtain,evenimpossible.Theengineeringapplicationofinversesystemcontroldoesn’tmeettheexpectations.Asneuralnetworkhasnon-linearapproximateability,especiallyfornonlinearcomplexitysystem,itbecomeswiththepowerfulexpectationstooltosolvetheproblem.a−thNNinversesystemintegratedinversesystemwithnon-linearabilityoftheneuralnetworkcanavoidthetroublesofinversesystemmethod.Thenitispossibletoapplyinversecontrolmethodtoacomplicatednon-linearsystem.a−thNNinversesystemmethodneedslesssysteminformationsuchastherelativeorderofsystem,anditiseasytoobtaintheinversemodelbyneuralnetworktraining.CascadingtheNNinversesystemwiththeoriginalsystem,apseudo-linearsystemiscompleted.Subsequently,alinearclose-loopregulatorwillbedesigned.

3.RealizationStepsofNeuralNetworkInverseSystem

3.1AcquisitionoftheInputandOutputTrainingSamples

Trainingsamplesareextremelyimportantinthereconstructionofneuralnetworkinversesystem.Itisnotonlyneedtoobtainthedynamicdataoftheoriginalsystem,butalsoneedtoobtainthestaticdate.Referencesignalshouldincludealltheworkregionoforiginalsystem,whichcanbeensuretheapproximateability.Firstlythestepofactuatingsignalisgivencorrespondingevery10HZform0HZto50HZ,andtheresponsesofopenloopareobtain.Secondlyarandomtanglesignalisinput,whichisarandomsignalcascadingonthestepofactuatingsignalevery10seconds,andthecloseloopresponsesisobtained.Basedontheseinputs,1600groupsshouldincludealltrainingsamplesaregotten.

3.2TheConstructionofNeuralNetwork

Astaticneuralnetworkandadynamicneuralnetworkcomposedofintegralisusedtoconstructtheinversesystem.Thestructureofstaticneuralnetworkis2neuronsininputlayer,3neuronsinoutputlayer,and12neuronsinhiddenlayer.Theexcitationfunctionofhiddenneuronismonotonicsmoothhyperbolictangentfunction.Theoutputlayeriscomposedofneuronwithlinearthresholdexcitationfunction.Thetrainingdatumarethecorrespondingspeedofopen-loop,close-loop,firstorderderivativeofthesespeed,andsettingreferencespeed.After50timestraining,thetrainingerrorofneuralnetworkachievesto0.001.Theweightandthresholdoftheneuralnetworkaresaved.Theinversemodelandadynamicneuralnetworkcomposedoforiginalsystemisobtained.

Inductionmotorvariablefrequencyspeed-regulatingsystemsuppliedbytheinverteroftrackingcurrentSPWMcanbeexpressedbynonlinearmodelind-qtwo-phaserotatingcoordinate.Themodelwassimplifiedasa3-ordernonlinear 

model.Whentheinverterisrunninginvectormode,thevariabilityoffluxlinkagecanbeneglected（considering 

the 

flux 

linkage 

to 

be 

invariableness 

and 

equal 

rating）.

4.ExperimentsandResults

4.1HardwareoftheSystem

ThehardwaresystemincludesuppercomputerinstalledwithSupervisory&

ControlconfigurationsoftwareWinCC6.0,andS7-300PLCofSIEMENS,inverter,inductioninstalledwithmotorandControlPhotoelectriccoder.

PLCcontrollerchoosesS7-315-2DP,whichhasaPROFIBUS-DPinterfaceandaMPIinterface.SpeedacquisitionmoduleisFM350-1.WinCCisconnectedwiththeexperimentsystemS7-300byCP5611usingMPIprotocol.

ThetypeofinverterisMMVofSIEMENS.ItcancommunicatewithSIEMENSPLCbyUSSprotocol.ACB15moduleisaddedontheinverterinthissystem.

4.2SoftwareProgram

4.2.1CommunicationIntroduction

MPI（MultiPointInterface）isasimpleandinexpensivecommunicationstrategyusinginslowlyandnon-largedatatransformingfield.ThedatatransformingbetweenWinCCandPLCisnotlarge,sotheMPIchosen.

TheMMVinverterisconnectedtothePROFIBUSnetworkasaslavestation,whichismountedwithCB15PROFIBUSmodule.PPO1orPPO3datatypecanbechosen.Itpermitstosendthecontroldatadirectlytotheinverteraddresses,ortousethesystemfunctionblocksofSTEP7V5.2SFC14/15.

OPCcanefficientlyprovidedataintegralandintercommunication.Differenttypeserversandclientscanaccessdatasourcesofeachother.Comparingwiththetraditionalmodeofsoftwareandhardwaredevelopment,equipmentmanufacturersonlyneedtodeveloponedriver.Thiscanshortthedevelopmentcycle,savemanpowerresources,andsimplifythestructuretheexperimentsystemoftheentirecontrolsystem.

VarietydataofthesystemisneededintheneuralnetworktrainingofMatlab,whichcannotobtainbyreadingfromPLCorWinCCdirectly.SoOPCtechnologycanbeusedtoobtaintheneededdatabetweenWinCCandExce.SettingWinCCasOPCDAserver,anOPCclientisconstructedinExcelbyVBA.SystemrealtimedataisreadedandwritentoExcelbyWinCC,andthenthedatainExcelistransformtoMatlabforofflinetrainingtogettheinversesystemoforiginalsystem.

4.2.2ControlProgram

UsedSTLtoprogramthecommunicationanddataacquisitionandcontrolalgorithmsubroutineinSTEP7V5.2,velocitysample