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1、NeuralNetworkStabilizingControlofSingleMachinePowerSystemwithControlLimitsWenxinLiu,JagannathanSarangapani,GaneshKVenayagamoorthy,DonaldCWunsch11,andMariesaLCrowElectricalandComputerEngineeringDepartment,UniversityofMissouri-Rolla,MO65401,USAEmails:wl3d@,umr.edu,saranrrap!&nx
2、.edu,eaneshvlii;umr.edu,dwunschi&hnr.edu.andcrm@unir.eduAbsfrucf-Powersystemstabilizersarewidelyusedtoannealing,geneticalgorithm,andtabusearch)areappliedgeneratesupplementarycontrolsignalsforthetoofilinedeterminingthe"optimalparameters"ofCPSSbyexcitationsysteminordertodampout
3、thelowoptimizinganeigenvaluebasedcostfunction.Inthepastfrequencyoscillations.Thispaperproposesastabledecade,fuzzylogicandNNwereappliedonlinetoadjustneuralnetwork(NN)controllerforthestabilizationofatheparametersofCPSSbasedontheknowledgegainedbysinglemachineinfinitebuspowersyst
4、em.Inthepowerofflinetraining,Sincepowersystemsarehighlynonlinearsystemcontrolliterature,simplifiedanalyticalmodelssystems,withconfigurationsandparameterschangingwithareusedtorepresentthepowersystemandthetime,thedesignsbasedonlinearizedmodelcannotcontrollerdesignsarenotbasedon
5、rigorousstabilityguaranteetheirperformancesinpracticaloperatinganalysis.Thispaperovercomesthetwomajorproblemsenvironment.Thus,adaptivecontrollerdesignsbasedonbyusinganaccurateanalyticalmodelforcontrollernonlinearmodelsarerequiredforthepowersystem[2].developmentandpresentsthec
6、losed-loopstabilityInrecentyears,stabilizingcontrolschemesusingNNandanalysis.TheNNisusedtoapproximatethecomplexfuzzylogichavebeenproposed.Mostofthepapersonlynonlinearpowersystemonlineandtheweightsofwhichdemonstratedtheeffectivenessofthecontrollerdesignviacanhesettozerotoavoid
7、thetimeconsumingofflinesimulationwhilenotthestabilityanalysis.Thereasonfortrainingprocess.MagnitudeconstraintoftheactivatorsismodeledassaturationnonlinearitiesandisincludedthelackofstabilityanalysisisduetothecomplexityoftheintheLyapnnovstabilityanalysis.Simulationresultspower
8、systems.Moreover,industywillhereluctanttodemonstratethattheproposedd
