赖氨酸发酵过程智能补料控制系统研究

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1、江苏大学硕士学位论文赖氨酸发酵过程智能补料控制系统研究姓名：丁慎平申请学位级别：硕士专业：农业电气化与自动化指导教师：孙玉坤20090607江苏大学硕士学位论文ABSTRACTLysineisoneofeightaminoacids．AnditiSanessentialnutrienttohumanbodybutcannotownasyntheticaminoacid．AlthoughLysineproductionwasabout700．000tonsinChinain2008．itsbasicrawmaterialproductionisstillinastateofgreatbu

2、tnotstrong．L—lysinefed—batchfermentationprocesscontroliSaflexibleandeffectivewaytocontrolthemiddleoflysinefermentationmetabolismandincreaseproduction．Fed—batchcontroliSthekeyfactorsofentirebatchfermentation．Theearlyfed—batchcontroliscompletelycarriedoutbyexperience．Thatistosay，thecontroliStoadda

3、certainamountofempiricalnutrientsinacertaintime．Ithascharacteristicsofsimpleingredients，smallnumberadditionandsimplemethod，butitCannotbecontrolledeffectively．Inthemodemlarge．scaleindustrialfermentation，thewayofthefed．batchhavedevelopedfromsimpletomulti．1evelrepeated，fromsimpleadditiontoseveralad

4、ditionalnutrients．Andnowfed．batchprocessalmostalltheempiricalandthetheoriesofresearcharelaggingbehind．TheitselfofmicrobialfermentationprocessiSacomplexanduncertain，non—lineartime-varyingdynamicprocess。whichinvolvesthelifegrowthandreproduction．Ithastoomanyimpactfactorsandcomplicatedmechanism．Beca

5、useofitsinherentcomplexitythefed．batchcontr01iSdi衢culttoachievethroughMechanismModeling．Inordertomakeupforthecurrentfed．batchfermentationcontroldisadvantagesthatover-relianceonmathematicalmodelsandrealizetheintelligentcontr01．Inthispaper，fuzzylogiccontroltheoryandneuralnetworktechnologywhichhass

6、elf-learningabilityarecombined．Theintelligentmicrobialfermentationfed-·batchcontrollerisdesignedbasedonthein·-depthstudyoffuzzyneuralnetwork．Basedonthe$3C44BOXofARMembeddedsystem．on—chipasthecore，thepaperhasdevelopedabio-fermentationbatchintelligentcontrolsystems，andoperatingsystemembedreal-time

7、operatingsystemtransplantation，whichcanimprovetheperformanceoffed．batchcontr01．ThesimulationresultshadbeenshownthatitiSaccuracyandrobustness．AndeffectivenessiSverifiedinlysinefermentationexperiment．Studyingonlysinefed．batchf