identification and control of continuous-time nonlinear systems via dynamic neural networks

identification and control of continuous-time nonlinear systems via dynamic neural networks

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时间:2019-03-03

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1、478IEEETRANSACTIONSONINDUSTRIALELECTRONICS,VOL.50,NO.3,JUNE2003IdentificationandControlofContinuous-TimeNonlinearSystemsviaDynamicNeuralNetworksX.M.Ren,A.B.Rad,P.T.Chan,andWaiLunLoAbstract—Inthispaper,wepresentanalgorithmfortheonlineMoreover,forunknownnonlinearsystems,thereisno

2、identificationandadaptivecontrolofaclassofcontinuous-timeeffectivemethodtodesignadaptivecontrollerstoensurenonlinearsystemsviadynamicneuralnetworks.Theplantcon-goodtrackingperformance.Recently,neuralnetworkshavesideredisanunknownmulti-input/multi-outputcontinuous-timebeenemploy

3、edintheidentificationandcontrolofunknownhigherordernonlinearsystem.Thecontrolschemeincludestwoparts:adynamicneuralnetworkisemployedtoperformsystemnonlinearsystemsowingtotheirmassiveparallelism,fastidentificationandacontrollerbasedontheproposeddynamicadaptationandlearningcapabil

4、ity[6]–[13].Untilnow,themostneuralnetworkisdevelopedtotrackareferencetrajectory.widelyusedneuralnetworkshavebeenfeedforwardneuralStabilityanalysisfortheidentificationandthetrackingerrorsnetworksanddynamicneuralnetworks.ManyresearchersuseisperformedbymeansofLyapunovstabilitycrit

5、erion.Finally,thefeedforwardneuralnetworksastherepresentationofaweillustratetheeffectivenessofthesemethodsbycomputersimulationsoftheDuffingchaoticsystemandone-linkrigidnonlinearoperatorintheright-handsideofthedynamicmodelrobotmanipulator.Thesimulationresultsdemonstratethattheeq

6、uation[6]–[8].Forexample,forthecontrolofunknownmodel-baseddynamicneuralnetworkcontrolschemeisappro-feedbacklinearizablecontinuous-timesystemswithrelativepriateforcontrolofunknowncontinuous-timenonlinearsystemsdegree,LiuandChen[7]employedthestaticfeedforwardwithoutputdisturbance

7、noise.neuralnetworkstomodelnonlinearfunctionsinthesystem.IndexTerms—Adaptivecontrol,continuous-timenonlinearsys-Thecontrollerwasdesignedbasedontheneuralnetworktems,dynamicneuralnetworks,systemidentification.modelstocontrolthesystemtotrackareferencetrajectory,andalocalconvergenc

8、eofthetrackingerrorwasalsodiscussed.I.INTRODUCTIONDesp

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