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1、ProceedingsoftheFifthInternationalConferenceonMachineLearningandCybernetics,Dalian,13-16August2006DIRECTADAPTIVECONTROLFORACLASSOFNONAFFINESYSTEMSYU-QIANGJIN,ZHI-CAIXIAO,JIN-HUAWUControlEngineeringDepartment,NavalAeronauticalEngineeringInstitute,Yantai26
2、4001,ChinaE-MAIL:jyq301@yahoo.com.cnAbstract:practice,isthatbasedonlinearizationofthenonlinearplantAdirectadaptivecontroldesignmethodisproposedforamodelaroundanoperatingpoint[7].classofuncertainsingle-inputsingle-output(SISO)nonaffineInthispaper,wediscus
3、stheadaptivedesignforaclasssystem.ItisadifficultproblemtobedealtwithinthecontrolofuncertainSISOnonaffinesystembasedonfuzzy-neuralliterature,mainlybecausethatthevirtualcontrolsandtheapproach.Toauthor’sknowledge,noeffectivemethodforfinalcontrollawofuncerta
4、innonaffinesystemisnoteasytothiscontrolproblemexistsintheliteratureatpresentstage.resolve.Toovercomethisdifficulty,thefuzzy-neuralThisismainlyduetothefactthatitisverydifficulttofindapproximatorcancelstheunknownpartoftheinversefunctionsadaptively.Then,Inv
5、ersedesign,backsteppingvirtualcontrolsintermsofinbacksteppingdesigndesign,andfeedbacklinearizationtechniquesareprocedure.Toovercomethisdifficulty,fuzzy-neuralincorporatedtodealwiththisproblem.Itisprovedthattheapproximatorisusedtoapproximatetheunknownpart
6、ofwholeclosed-loopsystemisstableinthesenseofLyapunov.inversefunctions.Inthefinalstep,feedbacklinearizationThecontrolperformanceisguaranteedbysuitablychoosingtechniquesandfuzzy-neuralapproximatorareusedtothedesignparameters.Simulationstudywasincludedtodes
7、ignthefinalcontrollaw.demonstratetheeffectivenessoftheproposedmethod.2.ProblemformulationKeywords:Nonaffinesystem;Adaptivecontrol;Backstepping;ThefollowinguncertainSISOnonaffinesystemsareFuzzy-neuralapproximatorconsideredinthispaper.1.Introductionx&iii=≤
8、fxx(),,i+11in≤−1,(1)Inrecentyears,controlsystemdesignforcomplexx&nnn=fxu(),,(2)nonlinearsystemshasattractedmuchattention.Manyy=x,(3)1remarkableresultsinthisareahavebeenobtained,Tiincludingfeedbacklinearizationtechniques,ad
