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基于LabVIEW和神经网络方法的在线温度控制系统研究.docx

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基于LabVIEW和神经网络方法的在线温度控制系统研究 Abstract Withtherapiddevelopmentoftechnology,thereisagrowingdemandfortheautomationoftemperaturecontrolsystemsinvariousapplications.ThispaperproposesanovelonlinetemperaturecontrolsystembasedonLabVIEWandneuralnetworkmethods.ThesystemconsistsofLabVIEWsoftwareandhardwaremodules,whichisusedtocollectandanalyzethetemperaturedataandcontrolthetemperaturebasedontheneuralnetworkmodel.Thesystemprovidesaconvenientwaytocontroltemperatureinvariousapplicationswithhighaccuracyandefficiency.Variousexperimentshavebeenconductedtovalidatetheeffectivenessoftheproposedsystem,andtheresultsdemonstratethattheproposedsystemcanachievebetterperformancecomparedtotraditionaltemperaturecontrolmethods. Introduction Thetemperaturecontrolsystemplaysacrucialroleinmanyfieldssuchaschemical,pharmaceutical,andbiotechnologyindustries.Accuratetemperaturecontrolisessentialtoensurethequalityoftheproductsandprocesssafety.TraditionaltemperaturecontrolsystemsrelyonPIDcontrollers,whichrequiremanualtuningandarelimitedtolinearsystems.Withthedevelopmentofneuralnetworktechnology,theonlinetemperaturecontrolsystembasedonLabVIEWandneuralnetworkmethodshasbeendeveloped,whichcanhandlenonlinearsystemsandprovidehigheraccuracy. Theproposedsystemconsistsoftwoparts:dataacquisitionandcontrol.Thedataacquisitionpartcollectsthetemperaturedataandsendsittothecontrolpart.Thecontrolpartanalyzesthetemperaturedataandsendsbackthecontrolsignalstoadjustthetemperature.Inthecontrolpart,aneuralnetworkmodelisusedtopredictthetemperature,andthecontrolsignalsaregeneratedbasedonthepredictedtemperature. NeuralNetworkModel Neuralnetworkmodelsarewidelyusedinnonlinearsystemidentificationandcontrol.Inthispaper,weusethebackpropagationalgorithmtotrainafeedforwardneuralnetworkmodel.Theinputoftheneuralnetworkisthetemperaturedata,andtheoutputisthepredictedtemperature.ThearchitectureoftheneuralnetworkisshowninFig.1. Theneuralnetworkhastwohiddenlayerswith20neuronsineachlayer.Thesigmoidfunctionisusedastheactivationfunctioninthehidden