简介:Operationaimofballmillgrindingprocessistocontrolgrindingparticlesizeandcirculationloadtoballmillintotheirobjectivelimitsrespectively,whileguaranteeingproducingsafelyandstably.Thegrindingprocessisessentiallyamulti-inputmulti-outputsystem(MIMO)withlargeinertia,strongcouplinganduncertaintycharacteristics.Furthermore,beingunabletomonitortheparticlesizeonlineinmostofconcentratorplants,itisdifficulttorealizetheoptimalcontrolbyadoptingtraditionalcontrolmethodsbasedonmathematicalmodels.Inthispaper,anintelligentoptimalcontrolmethodwithtwo-layerhierarchicalconstructionispresented.Basedonfuzzyandrule-basedreasoning(RBR)algorithms,theintelligentoptimalsettinglayergeneratestheloopssetpointsofthebasiccontrollayer,andthelattercantracktheirsetpointswithdecentralizedPIDalgorithms.Withthedistributedcontrolsystem(DCS)platform,theproposedcontrolmethodhasbeenbuiltandimplementedinaconcentrationplantinGansuprovince,China.Theindustrialapplicationindicatesthevalidationandeffectivenessoftheproposedmethod.
简介:Arecursiveidentificationmethodisproposedtoobtaincontinuous-timestate-spacemodelsinsystemswithnonuniformlysampled(NUS)data.Duetothenonuniformsamplingfeature,thetimeintervalfromonerecursionsteptothenextvariesandtheparameterisalwaysupdatedpartiallyateachstep.Furthermore,thisidentificationmethodisappliedtoformacombineddatacompressionmethodinNUSprocesses.Thedatatobecompressedarefirstclassifiedwithrespecttoaseriesofpotentiallyexisting(possiblytime-varying)models,andthenmodeledbytheNUSidentificationmethod.Themodelparametersarestoredinsteadoftheidentificationoutputdata,whichmakesthefirstcompression.Subsequently,asthesecondstep,theconventionalswingingdoortrendingmethodiscarriedoutonthedatafromthefirststep.Numericresultsfromsimulationaswellaspracticaldataaregiven,showingtheeffectivenessoftheproposedidentificationmethodandfoldincreaseofcompressionratioachievedbythecombineddatacompressionmethod.