简介：Inthispaper,byusingthewell-knownhigh-gainobserverdesign,anupdatelawforthegainandanadaptiveestimationofparameters,anewmethodoffaultdiagnosisforaclassofnonlinearsystemsispresented.Withoutresorttoanytransformationfortheparameters,theestimationerrorsofthestatesandtheparametersareguaranteedtobegloballyexponentiallyconvergentbyapersistentexcitationcondition.Comparedtotheexistingresults,itcanbeappliedtononlinearsystemswithnonlineartermsadmittinganincrementalratedependingonthemeasuredoutput.Acasestudyfurtherverifiesthevalidityoftheproposedresearch.

简介：Thispaperdealswiththedesignofanoutputfeedbackpredictivecontrollerforinductionmotors.Thefundamentalinterestoftheproposedcontrolleristhecapabilityofdecouplingthemechanicalspeedandtherotorfluxes,withoutdegradationagainstthevariationofrotorresistanceandloadtorque.Hence,thecontributionistoapplytwoestimationproceduresinordertoachievethisgoal.Namely,anunknowninputobserver（UIO）isusedfortheconstanttimeestimationwhereasaheuristicsolutionisexploitedfortheloadtorqueupdate.Moreover,rotorfluxcomponentsarerecoveredasanunavailablestateofthesystem.Effectivenessoftheproposedobserversandtheperformanceofthecontrollerareconfirmedbysimulationresults.