Observer-Based Adaptive Fuzzy Backstepping Output Feedback Control of Uncertain MIMO Pure-Feedback Nonlinear Systems

Observer-Based Adaptive Fuzzy Backstepping Output Feedback Control of Uncertain MIMO Pure-Feedback Nonlinear Systems

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时间:2019-11-27

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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.Thefilteredsignalstigated,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

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