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ID:31977580
大小:2.19 MB
页数:66页
时间:2019-01-29
《基于多目标优化算法的发酵过程控制方法.研究》由会员上传分享,免费在线阅读,更多相关内容在教育资源-天天文库。
1、一些!坠生!..●_---___________-——————___————————-●__—————————-●-————————————●-________________________--_—_——————————————————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_=大学硕上学位论文controlmethodforfed-batchfermentationprocesswasgiventodeterminetheoptimalfeedprofilesperiodically.Throughtheconcreteexperimentandanalysis,thefeasibil
7、ityandvalidityofproposedmethodwasverified.Theexperimentalresultsshowthatthesearchabilityneartheconstraintsborderwithproposedself-adaptiveevolutionaryconstrainedmulti—objectiveparticleswarmoptimizationalgorithmisgreatlyincreased,andthedistributionofParetofro
8、ntisimprovedobviouslywithoutanyincreaseinthecomplexityofalgorithm.Theon—lineoptimizationcontrolmethodforfermentationprocessbasedOnmulti—objectiveparticleswarmalgorithmcanmaketheoptimizationresultbetter
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