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1、一些!墜生!．．●_---___________-——————___————————-●__—————————-●-————————————●-________________________--_—_——————————————————一ResearchonOptimalControlMethodforFermentationProcessBasedMulti—objectiveOptimizationAlgorithmABSTRACTTheoptimizationoffermentationprocess
2、isofgreateffecttoimprovetheproductionefficiency．Thefermentationprocessisanonlinearandtime—varyingsystem，andtheoptimizationprobleminfermentationprocessisessentiallyamulti—objectiveoptimizationproblemwithconstraintswhichisdifficulttobesolvedbytheoptimalcontro
3、ltheoryandtraditionaloptimizationmethod．Multi—objectiveparticleswarmoptimizationalgorithmbasedonrandomsearchstrategyisverysuitabletosolvecomplexnonlinearmulti—objectiveoptimizationprobleminfermentationprocessduetoitshighsearchefficiencyandgoodrobustness．The
4、refore，itisofacademicsignificancetoresearchontheoptimalcontrolforfermentationprocessbasedonthemulti—objectiveparticleswarmoptimizationalgorithm．Basedontheanalysisofthemulti—objectiveparticleswarmoptimizationalgorithm，aself-adaptiveevolutionaryconstrainedmul
5、ti—objectiveparticleswarmoptimizationalgorithmwasproposed．GiventheinvarianceoftheParetooptimalsolutionspositionwithinanevolution，adynamiccrowdingdiversitymaintenancestrategybasedonpositioninformationwasadopted．Akindofmulti··objectivedecision·-makingmethodfo
6、rfed--batchfermentationprocesswaspresented．Onthisbasis，anon—linemulti—objectiveoptimization1II北京化1_=大學(xué)碩上學(xué)位論文controlmethodforfed-batchfermentationprocesswasgiventodeterminetheoptimalfeedprofilesperiodically．Throughtheconcreteexperimentandanalysis，thefeasibil
7、ityandvalidityofproposedmethodwasverified．Theexperimentalresultsshowthatthesearchabilityneartheconstraintsborderwithproposedself-adaptiveevolutionaryconstrainedmulti—objectiveparticleswarmoptimizationalgorithmisgreatlyincreased，andthedistributionofParetofro
8、ntisimprovedobviouslywithoutanyincreaseinthecomplexityofalgorithm．Theon—lineoptimizationcontrolmethodforfermentationprocessbasedOnmulti—objectiveparticleswarmalgorithmcanmaketheoptimizationresultbetter
