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1、Proceedingsofthe10thWorldCongressonIntelligentControlandAutomationJuly6-8,2012,Beijing,ChinaAModifiedFruit-FlyOptimizationAlgorithmAidedPIDControllerDesigning*YiLiu,XuejieWang,YanjunLiSchoolofInformation&ElectricalEngineering,ZhejiangUniversityCityCollege,Hangzhou,China978
2、355734@qq.com,{xjwang,liyanjun}@zucc.edu.cnAbstract-FruitFlyOptimizationAlgorithm(FOA)isoneoflocationonpurposetoimproveitsdiversity.thenewestintelligentoptimizationalgorithms.AttractedbyitsòTheupdatingstrategyofPSOalgorithmisintroducedsimpleimplementprocedurewitheffectives
3、earchingcapability,toreducetheblindnessofFOAinsolutionsearching.ourworkistopopularizethisalgorithmtotacklesomepracticalòSimulatedAnnealing(SA)isutilizedasalocalsearchoptimizationapplicationsrequestingreal-timeperformance.However,theupdatingstrategyofFOAiswithstrongtooltohe
4、lpthecandidatesolutionspursuingbetterrandomness,thusbringinginsomeblindnesssearchinginoptimalresult.solutionupdating,whichwillresultinslowconvergencerateandInordertoverifytheperformanceofMFOA,wechoosepremature.Therefore,amodifiedFOA(MFOA)basedonPSOtwocommontestingfunctions
5、andamulti-parametersandSAwasproposedinthispapertoimprovetheperformanceoptimizationproblem(PIDcontrollerparametersofbasicFOA.Besides,Chaosfuntionwasusedtoenhancetheoptimization)astestingobjects.PIDcontrollerparametersstochasticandergodicfeaturesofinitialsolutionsoastoimprov
6、ethediversityofinitialpopulationinMFOA.PSOisintroducedtoselectioncanbeviewedasacontinuousoptimizationproblem.reducetheblindnesssearchinginsolutionupdating.SAisusedasBasedonintelligentoptimizationalgorithms,R.A.Krohlingalocalsearchtoimprovetheconvergencerate.Finally,inorder
7、etal.(2001)presentedthedesignofoptimaldistancerejectiontoverifytheefficiencyofMFOAalgorithm,twocommonPIDcontrollerbasedonGA[8];Z.L.Gaing(2004)putfunctionsandapracticalhigh-orderAVRsystemwithPIDforwardaPSOapproachforthedesignofPIDcontrollerincontrollerweretestedinsimulation
8、.ExperimentalresultsAVRsystem[9];RongjongWaietal.(2011)suppliedPSOinrevealedtheencouragin
