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1、IEEETRANSACTIONSONFUZZYSYSTEMS,VOL.20,NO.4,AUGUST2012771Observer-BasedAdaptiveFuzzyBacksteppingOutputFeedbackControlofUncertainMIMOPure-FeedbackNonlinearSystemsShaochengTong,YongmingLi,andPengShi,SeniorMember,IEEEAbstractThispaperisconcernedwiththeproblemofadap-systemsareavailableformea
2、surementintheaforementionedtivefuzzytrackingcontrolforaclassofuncertainmultiple-inputcontrolapproaches,in[19][28],theproblemofadaptivefuzzymultiple-output(MIMO)pure-feedbacknonlinearsystemswithorneuraloutputfeedbackcontrolforuncertainSISO,MIMO,orimmeasurablestates.Thedynamicoutputfeedba
3、ckstrategybe-large-scalenonlinearsystemviastateobservershasbeeninves-ginswithastateobserver.Fuzzylogicsystemsareutilizedtoap-proximatetheunknownnonlinearfunctions.The?lteredsignalstigated,andthestabilityoftheresultingclosed-loopadaptiveareintroducedtocircumventalgebraicloopproblemencoun
4、teredcontrolsystemhasbeenanalyzed.Ingeneral,adaptivefuzzyintheimplementationofthecontroller,andanadaptivefuzzyout-orneuralnetworkbacksteppingcontrolprovidesasystematicputfeedbackisobtainedviaabacksteppingrecursivedesigntech-methodtosolvetrackingorregulationcontrolproblemsofun-nique.Itis
5、shownthattheproposedcontrollawcanguaranteethatknownnonlinearsystems,wherefuzzylogicsystems(FLSs)allthesignalsoftheresultingclosed-loopsystemaresemigloballyuniformlyultimatelyboundedandthattheobserverandtrackingorneuralnetworksareusedtoapproximateunknownnonlinearerrorsconvergetoasmallnei
6、ghborhoodoftheorigin.Simulationfunctions[29][34].Typically,adaptivefuzzyorneuralnet-studiesareincludedtoillustratetheeffectivenessandpotentialsofworkcontrollersareconstructedrecursivelyintheframeworktheproposedtechniques.ofatraditionalbacksteppingdesigntechnique[35][37].TwoIndexTermsAda
7、ptiveoutputfeedbackcontrol,backsteppingofthemainfeaturesoftheseadaptiveapproachesincludethedesign,fuzzylogicsystems(FLSs),nonlinearmultiple-inputfollowing:1)Theyhandlethosenonlinearsystemswithoutthemultiple-output(MIMO)systems,stateobserver.requirementofmatchingcondition,and2)t