堆垛机英文资料翻译Word格式.docx
- 文档编号:18774229
- 上传时间:2023-01-01
- 格式:DOCX
- 页数:13
- 大小:142.87KB
堆垛机英文资料翻译Word格式.docx
《堆垛机英文资料翻译Word格式.docx》由会员分享,可在线阅读,更多相关《堆垛机英文资料翻译Word格式.docx(13页珍藏版)》请在冰豆网上搜索。
Theneuralnetworkinversesystem[4][5]isanovelcontrolmethodinrecentyears.Thebasicideaisthat:
foragivensystem,aninversesystemoftheoriginalsystemiscreatedbyadynamicneuralnetwork,andthecombinationsystemofinverseandobjectistransformedintoakindofdecouplingstandardizedsystemwithlinearrelationship.Subsequently,alinearclose-loopregulatorcanbedesignedtoachievehighcontrolperformance.Theadvantageofthismethodiseasilytoberealizedinengineering.Thelinearizationanddecouplingcontrolofnormalnonlinear
systemcanrealizeusingthismethod.
CombiningtheneuralnetworkinverseintoPLCcaneasilymakeuptheinsufficiencyofsolvingtheproblemsofnonlinearandcouplinginPLCcontrolsystem.Thiscombinationcanpromotetheapplicationofneuralnetworkinverseintopracticetoachieveitsfulleconomicandsocialbenefits.
Inthispaper,firstlytheneuralnetworkinversesystemmethodisintroduced,andmathematicmodelofthevariablefrequencyspeed-regulatingsysteminvectorcontrolmodeispresented.Thenareversibleanalysisofthesystemisperformed,andthemethodsandstepsaregiveninconstructingNN-inversesystemwithPLCcontrolsystem.Finally,themethodisverifiedinexperiments,andcomparedwith
traditionalPIcontrolandNN-inversecontrol.
2.NeuralNetworkInverseSystemControlMethod
Thebasicideaofinversecontrolmethod[6]isthat:
foragivensystem,anα-thintegralinversesystemoftheoriginalsystemiscreatedbyfeedbackmethod,andcombiningtheinversesystemwithoriginalsystem,akindofdecouplingstandardizedsystemwithlinearrelationshipisobtained,whichisnamedasapseudolinearsystemasshowninFig.1.Subsequently,alinearclose-loopregulatorwillbedesignedtoachievehighcontrolperformance.
Inversesystemcontrolmethodwiththefeaturesofdirect,simpleandeasytounderstanddoesnotlikedifferentialgeometrymethod[7],whichisdiscussestheproblemsin"
geometrydomain"
.Themainproblemistheacquisitionoftheinversemodelintheapplications.Sincenon-linearsystemisacomplexsystem,anddesiredstrictanalyticalinverseisverydifficulttoobtain,evenimpossible.Theengineeringapplicationofinversesystemcontroldoesn’tmeettheexpectations.Asneuralnetworkhasnon-linearapproximateability,especiallyfornonlinearcomplexitysystem,itbecomesthepowerfultooltosolvetheproblem.a−thNNinversesystemintegratedinversesystemwithnon-linearabilityoftheneuralnetworkcanavoidthetroublesofinversesystemmethod.Thenitispossibletoapplyinversecontrolmethodtoacomplicatednon-linearsystem.a−thNNinversesystemmethodneedslesssysteminformationsuchastherelativeorderofsystem,anditiseasytoobtaintheinversemodelbyneuralnetworktraining.CascadingtheNNinversesystemwiththeoriginalsystem,apseudo-linearsystemiscompleted.Subsequently,alinearclose-loopregulatorwillbedesigned.
3.MathematicModelofInductionMotorVariableFrequencySpeed-RegulatingSystemandItsReversibility
Inductionmotorvariablefrequencyspeed-regulatingsystemsuppliedbytheinverteroftrackingcurrentSPWMcanbeexpressedby5-thordernonlinearmodelind-qtwo-phaserotatingcoordinate.Themodelwassimplifiedasa3-ordernonlinearmodel.Ifthedelayofinverterisneglected,
themodelisexpressedasfollows:
(1)
where
denotessynchronousanglefrequency,and
isrotatespeed.
arestator’scurrent,and
arerotor’sfluxlinkagein
(d,q)axis.
isnumberofpoles.
ismutualinductance,and
isrotor’sinductance.Jismomentofinertia.
isrotor’stimeconstant,and
isloadtorque.
Invectormode,then
Substituteditintoformula
(1),then
(2)
Takingreversibilityanalysesofforum
(2),then
Thestatevariablesarechosenasfollows
Inputvariablesare
Takingthederivativeonoutputinformula(4),then
(5)
(6)
ThentheJacobimatrixisRealizationofNeuralNetworkInverseSystemwithPLC
(7)
(8)
As
so
andsystemisreversible.Relative-orderofsystemis
Whentheinverterisrunninginvectormode,thevariabilityoffluxlinkagecanbeneglected(consideringthefluxlinkagetobeinvariablenessandequaltotherating).Theoriginalsystemwassimplifiedasaninputandanoutputsystemconcludedbyforum
(2).
Accordingtoimplicitfunctionontologytheorem,inversesystemofformula(3)
canbeexpressedas
(9)
Whentheinversesystemisconnectedtotheoriginalsysteminseries,thepseudolinearcompoundsystemcanbebuiltasthetypeof
4.RealizationStepsofNeuralNetworkInverseSystem
4.1AcquisitionoftheInputandOutputTrainingSamples
Trainingsamplesareextremelyimportantinthereconstructionofneuralnetworkinversesystem.Itisnotonlyneedtoobtainthedynamicdataoftheoriginalsystem,butalsoneedtoobtainthestaticdate.Referencesignalshouldincludealltheworkregionoforiginalsystem,whichcanbeensuretheapproximateability.Firstlythestepofactuatingsignalisgivencorrespondingevery10HZform0HZto50HZ,andtheresponsesofopenloopareobtain.Secondlyarandomtanglesignalisinput,whichisarandomsignalcascadingonthestepofactuatingsignalevery10seconds,andthecloseloopresponsesisobtained.Basedontheseinputs,1600groups
trainingsamplesaregotten.
4.2TheConstructionofNeuralNetwork
Astaticneuralnetworkandadynamicneuralnetworkcomposedofintegralisusedtoconstructtheinversesystem.Thestructureofstaticneuralnetworkis2neuronsininputlayer,3neuronsinoutputlayer,and12neuronsinhiddenlayer.Theexcitationfunctionofhiddenneuronismonotonicsmoothhyperbolictangentfunction.Theoutputlayeriscomposedofneuronwithlinearthresholdexcitationfunction.Thetrainingdatumarethecorrespondingspeedofopen-loop,close-loop,firstorder
derivativeofthesespeed,andsettingreferencespeed.After50timestraining,thetrainingerrorofneuralnetworkachievesto0.001.Theweightandthresholdoftheneuralnetworkaresaved.Theinversemodeloforiginalsystemisobtained.
5.ExperimentsandResults
5.1HardwareoftheSystem
ThehardwareoftheexperimentsystemisshowninFig5.ThehardwaresystemincludesuppercomputerinstalledwithSupervisory&
ControlconfigurationsoftwareWinCC6.0[8],andS7-300PLCofSIEMENS,inverter,inductionmotorandphotoelectriccoder.
PLCcontrollerchoosesS7-315-2DP,whichhasaPROFIBUS-DPinterfaceandaMPIinterface.SpeedacquisitionmoduleisFM350-1.WinCCisconnectedwithS7-300byCP5611usingMPIprotocol.
ThetypeofinverterisMMVofSIEMENS.ItcancommunicatewithSIEMENSPLCbyUSSprotocol.ACB15moduleisaddedonthe
inverterinthissystem.
5.2SoftwareProgram
5.2.1CommunicationIntroduction
MPI(MultiPointInterface)isasimpleandinexpensivecommunicationstrategyusinginslowlyandnon-largedatatransformingfield.ThedatatransformingbetweenWinCCandPLCisnotlarge,sotheMPIprotocolis
chosen.
TheMMVinverterisconnectedtothePROFIBUSnetworkasaslavestation,whichismountedwith
- 配套讲稿:
如PPT文件的首页显示word图标,表示该PPT已包含配套word讲稿。双击word图标可打开word文档。
- 特殊限制:
部分文档作品中含有的国旗、国徽等图片,仅作为作品整体效果示例展示,禁止商用。设计者仅对作品中独创性部分享有著作权。
- 关 键 词:
- 堆垛 英文 资料 翻译