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Transcription:

HistoricalPerspective RobertDMiddlebrook PhD,Standford,1955 CalTech Professor,19551998 SlobodanCúk PhDCalTech,1976 CalTech Prof,19771999 Modelaswitchedsystemasan averaged,timeinvariantsystemwith where A.R.BrownandR.D.Middlebrook, SampleddataModelingofSwitchingRegulators PESC1981 LinearCircuitModelingUsingStateSpace Inswitchposition1

LinearCircuitModelingUsingStateSpace Inswitchposition1 Whichcanbewritten,instatespace,formas Or,generally, Inthesecondswitchposition,wewillhaveanew(linear)circuitwith SwitchingSignal InaPWMconverterwithtwo switchpositions,thetwolinear circuitscombineaccordingtoa switchingfunction s(t) 1 0 where

SMPSStateSpace Intraditionalstatespacemodelingoflinearsystems withu(t) containingacontrolinput.whena andb areconstant, thisisalinearsystem.however,wehave or,equivalently whichisnonlinear:howdowedealwithit? ConvertingtoLinearSystem Assumethatoursystemmodel canbeapproximatedbysomelinearsystem whichremovesthenonlinearityofthesystem Nonlinearitiescamefromswitching Expectthatswitchingdynamicswillbelost Note:Thissystemisnowlinearin and,butnotinour controlsignal,

ApproximateSteadyStateWaveforms ApproximateSteadyStateWaveforms

ApproximateSteadyStateWaveforms TheAveragingApproximation Ifwaveformscanbeapproximatedaslinear sotheaverageslopeis or,rearranging

TheAveragedSystem Thisequationisnowthemodelofanew,equivalent linearsystem where whichhasaveragedbehavioroveroneswitching period Thisapproximationisperhaps valid,if Statewaveformsaredominantlylinear Dynamicsofinterestareat BuckStateSpaceAveraging Inswitchposition1 Inswitchposition2

BuckAveragedModel So,ouraveragemodelis = Averaging:Discussion

DiscreteTimeNatureofPWM DiscreteTimeNatureofPWM

DiscreteTimeNatureofPWM HistoricalPerspective RobertDMiddlebrook PhD,Standford,1955 CalTech Professor,19551998 SlobodanCúk PhDCalTech,1976 CalTech Prof,19771999 Modelaswitchedsystemasan averaged,timeinvariantsystemwith where DennisJohnPackard PhD,CalTech 1976 Modelaswitchedsystemasadiscretetime systemwith where A.R.BrownandR.D.Middlebrook, SampleddataModelingofSwitchingRegulators PESC1981

LargeSignalModelingofSMPS DiscreteTimeModeling Everysubcircuit isapassive,linearcircuit Passive,linearcircuitscanbesolvedinclosed form Canmodelstatesatdiscretetimeswithout averaging Onlyassumptionsrequired IndependentinputsareDCorslowlyvarying

SolutiontoStateSpaceEquation Closedformsolutiontostatespaceequation Multiplybothsidesby Lefthandsideis SolutiontoStateSpaceEquation Cannowbesolvedbydirectintegration Rearranging

MatrixExponential MatrixexponentialdefinedbyTaylorseriesexpansion Wellknownissuewithconvergenceinmanycases N C.Moler andc.v.loan, Nineteendubiouswaystocomputetheexponentialofamatrix, SIAMReview,vol.20,pp. 801 836,1978. PropertiesoftheMatrixExponential Matrixexponentialalwaysexists i.e.summationwillalwaysconverge Exponentialofanymatrixisalwaysinvertible, with

FirstOrderTaylorSeriesExpansion Linearrippleapproximation Validonlyifswitchingfrequencymuchfaster thansystemmodes SimplificationforSlowVaryingInputs IfAisinvertibleand

ApplicationtoSwitchingConverter ApplicationtoSwitchingConverter

ApplicationtoSwitchingConverter ApplicationtoSwitchingConverter

ApplicationtoSwitchingConverter GeneralForm Generally,for separateswitchingpositions Equationisintheformofadiscretetimesystemwith Again,theeffectofchangingmodulation(i.e. )ishiddeninnonlinearterms Find bysmallsignalmodeling