簡介：ARXIV10035062V1PHYSICSGENPH26MAR2010AUTOMATICPOLISHINGPROCESSOFPLASTICINJECTIONMOLDSONA5AXISMILLINGCENTERJOURNALOFMATERIALSPROCESSINGTECHNOLOGYXAVIERPESSOLES,CHRISTOPHETOURNIERLURPA,ENSCACHAN,61AVDUPDTWILSON,94230CACHAN,FRANCECHRISTOPHETOURNIERLURPAENSCACHANFR,TEL33147402996,FAX33147402211ABSTRACTTHEPLASTICINJECTIONMOLDMANUFACTURINGPROCESSINCLUDESPOLISHINGOPERATIONSWHENSURFACEROUGHNESSISCRITICALORMIRROREFFECTISREQUIREDTOPRODUCETRANSPARENTPARTSTHISPOLISHINGOPERATIONISMAINLYCARRIEDOUTMANUALLYBYSKILLEDWORKERSOFSUBCONTRACTORCOMPANIESINTHISPAPER,WEPROPOSEANAUTOMATICPOLISHINGTECHNIQUEONA5AXISMILLINGCENTERINORDERTOUSETHESAMEMEANSOFPRODUCTIONFROMMACHININGTOPOLISHINGANDREDUCETHECOSTSWEDEVELOPSPECIALALGORITHMSTOCOMPUTE5AXISCUTTERLOCATIONSONFREEFORMCAVITIESINORDERTOIMITATETHESKILLSOFTHEWORKERSTHESEAREBASEDONBOTHFILLINGCURVESANDTROCHOIDALCURVESTHEPOLISHINGFORCEISENSUREDBYTHECOMPLIANCEOFTHEPASSIVETOOLITSELFANDSETUPBYCALIBRATIONBETWEENDISPLACEMENTANDFORCEBASEDONAFORCESENSORTHECOMPLIANCEOFTHETOOLHELPSTOAVOIDKINEMATICALERROREFFECTSONTHEPARTDURING5AXISTOOLMOVEMENTSTHEEFFECTIVENESSOFTHEMETHODINTERMSOFTHESURFACEROUGHNESSQUALITYANDTHESIMPLICITYOFIMPLEMENTATIONISSHOWNTHROUGHEXPERIMENTSONA5AXISMACHININGCENTERWITHAROTARYANDTILTTABLEKEYWORDSAUTOMATICPOLISHING,5AXISMILLINGCENTER,MIRROREFFECT,SURFACEROUGHNESS,HILBERT’SCURVES,TROCHOIDALCURVES1SURFACEROUGHNESSPARAMETERSRAARITHMETICAVERAGEDEVIATIONOFTHESURFACE2DSAARITHMETICALMEANHEIGHTOFTHESURFACE3DSQROOTMEANSQUAREDEVIATIONOFTHESURFACESSKSKEWNESSOFTOPOGRAPHYHEIGHTDISTRIBUTIONSKUKURTOSISOFTOPOGRAPHYHEIGHTDISTRIBUTION3

簡介：英文翻譯系別自動化系專業(yè)自動化班級191003學(xué)生姓名周兵學(xué)號103658指導(dǎo)教師聶聰1引言萬向者往往是在當(dāng)代運(yùn)用戰(zhàn)術(shù)導(dǎo)彈。他們應(yīng)該提供快速，準(zhǔn)確的由目標(biāo)檢測器產(chǎn)生的視軸誤差信號的跟蹤設(shè)在內(nèi)部萬向支架，在導(dǎo)引頭控制的要求更為嚴(yán)重的結(jié)局部分參與。性能結(jié)果丟失的距離不夠大因此降低了一個成功的截取的概率。一個兩自由度的（2DOF）的速率陀螺儀通常安裝在內(nèi)部萬向支架，并直接饋送慣性角速率，以扭矩裝置提供瞄準(zhǔn)誤差跟蹤和穩(wěn)定反對基地運(yùn)動1，2。后者是導(dǎo)彈的角和直線運(yùn)動的參與過程的結(jié)果并通過機(jī)械裝置傳送到平衡環(huán)。準(zhǔn)確的尋求穩(wěn)定的成像是至關(guān)重要的減少圖像涂抹,足夠的目標(biāo)獲取,進(jìn)而影響分割和跟蹤。此外,小質(zhì)量的平衡增加干擾的平衡環(huán)的導(dǎo)彈加速度。在戰(zhàn)術(shù)導(dǎo)彈子系統(tǒng)的包裝嚴(yán)重受容積和空氣動力學(xué)限制，最終規(guī)定的可操作性。萬向求職者通常定位在導(dǎo)彈的前末端。不是很少的大小導(dǎo)引頭及其配套制度決定的形狀導(dǎo)彈的前部尖端。在這種情況下，形狀笨重，更激烈成為產(chǎn)生沖擊波的降低導(dǎo)彈的性能。導(dǎo)引頭可以通過減少從萬向部件卸下速率陀螺和使用一個捷聯(lián)式結(jié)構(gòu)。然而，這種方法要求內(nèi)部萬向支架角速率相對于該的估計彈體。的相對角速度分化萬向節(jié)，并進(jìn)一步匹配濾波，以減少噪音一直在一個線性化方法中使用3，以穩(wěn)定的單一軸萬向成像導(dǎo)引頭的運(yùn)動不安。不正確由圖像分割算法的輸出被忽視?；？刂埔咽褂?下的假設(shè)的非耦合相同俯仰和偏航通道再次單軸萬向?qū)б^和評價對代表命令信號。需要提出的控制律的第一和第二時間導(dǎo)數(shù)的計算命令信號，以及萬向架的完美測量角位移和相對彈體率。本文提出延長上述配方，以應(yīng)付具有偏航和俯仰控制成像的動態(tài)導(dǎo)引頭。該方法是基于模型的非線性與在其隨時間變化的慣性導(dǎo)引頭使用動態(tài)擴(kuò)展卡爾曼濾波（EKF），針對的估計相對角位移的平衡環(huán)。此外，圖像序列分析，假設(shè)目標(biāo)分割已經(jīng)解決，并在其質(zhì)心位置的有噪聲估計圖像平面是可供在光學(xué)方面解決流21估計的視覺反饋的扭矩裝置。該方法是通過評估與脫靶的統(tǒng)計評估通過蒙特卡羅模擬閉環(huán)包括導(dǎo)引頭的控制和戰(zhàn)術(shù)十字形的動態(tài)模型導(dǎo)彈。該導(dǎo)彈是由純

簡介：PSEUDOPOLARBASEDESTIMATIONOFLARGETRANSLATIONSROTATIONSANDSCALINGSINIMAGESYOSIKELLERAMIRAVERBUCHMOSHEISRAELIDEPARTMENTOFMATHEMATICSDEPARTMENTOFCOMPUTERSCIENCEDEPARTMENTOFCOMPUTERSCIENCEYALEUNIVRSITYTELAVIVUNIVERSITYTECHNIONINSTITUTEOFTECHNOLOGYNEWHAVEN,CT,USATELAVIV,ISRAELHAIFA,ISRAELYOSIKELLERYALEEDUABSTRACTONEOFTHEMAJORCHALLENGESRELATEDTOIMAGEREGISTRATIONISTHEESTIMATIONOFLARGEMOTIONSWITHOUTPRIORKNOWLEDGETHISPAPERPRESENTSAFOURIERBASEDAPPROACHTHATESTIMATESLARGETRANSLATION,SCALEANDROTATIONMOTIONSTHEALGORITHMUSESTHEPSEUDOPOLARTRANSFORMTOACHIEVESUBSTANTIALIMPROVEDAPPROXIMATIONSOFTHEPOLARANDLOGPOLARFOURIERTRANSFORMSOFANIMAGETHUS,ROTATIONANDSCALECHANGESAREREDUCEDTOTRANSLATIONSWHICHAREESTIMATEDUSINGPHASECORRELATIONBYUTILIZINGTHEPSEUDOPOLARGRIDWEINCREASETHEPERFORMANCEACCURACY,SPEED,ROBUSTNESSOFTHEREGISTRATIONALGORITHMSSCALESUPTO4ANDARBITRARYROTATIONANGLESCANBEROBUSTLYRECOVERED,COMPAREDTOAMAXIMUMSCALINGOF2RECOVEREDBYTHECURRENTSTATEOFTHEARTALGORITHMSTHEALGORITHMUTILIZESONLY1DFFTCALCULATIONSWHOSEOVERALLCOMPLEXITYISSIGNIFICANTLYLOWERTHANPRIORWORKSEXPERIMENTALRESULTSDEMONSTRATETHEAPPLICABILITYOFTHESEALGORITHMS1INTRODUCTIONIMAGEREGISTRATIONPLAYSAVITALROLEINMANYIMAGEPROCESSINGAPPLICATIONSSUCHASVIDEOCOMPRESSION1,VIDEOENHANCEMENT2ANDSCENEREPRESENTATION3TONAMEAFEWTHISPROBLEMWASANALYZEDUSINGVARIOUSCOMPUTATIONALTECHNIQUES,SUCHASPIXELDOMAINGRADIENTMETHODS2,CORRELATIONTECHNIQUES15ANDDISCRETEFOURIERDFTDOMAINALGORITHMS6,11GRADIENTMETHODSBASEDIMAGEREGISTRATIONALGORITHMSARECONSIDEREDTOBETHESTATEOFTHEARTTHEYMAYFAILUNLESSTHETWOIMAGESAREMISALIGNEDBYONLYAMODERATEMOTIONFOURIERBASEDSCHEMES,WHICHAREABLETOESTIMATERELATIVELYLARGEROTATION,SCALINGANDTRANSLATION,AREOFTENUSEDASBOOTSTRAPFORMOREACCURATEGRADIENTMETHODSTHEBASICNOTIONRELATEDTOFOURIERBASEDSCHEMESISTHESHIFTPROPERTY18OFTHEFOURIERTRANSFORMWHICHALLOWSROBUSTESTIMATIONOFTRANSLATIONSUSINGTHENORMALIZEDPHASECORRELATIONALGORITHM6,9,10HENCE,INORDERTOACCOUNTFORROTATIONSANDSCALING,THEIMAGEISTRANSFORMEDINTOAPOLARORLOGPOLARFOURIERGRIDREFERREDTOASTHEFOURIERMELLINTRANSFORMROTATIONSANDSCALINGAREREDUCEDTOTRANSLATIONSINTHESEREPRESENTATIONSANDCANBEESTIMATEDUSINGPHASECORRELATIONINTHISPAPERWEPROPOSETOITERATIVELYESTIMATETHEPOLARANDLOGPOLARDFTUSINGTHEPSEUDOPOLARFFTPPFFT19THERESULTINGALGORITHMISABLETOROBUSTLYREGISTERIMAGESROTATEDBYARBITRARYANGLESANDSCALEDUPTOAFACTOROF4ITSHOULDBENOTEDTHATTHEMAXIMUMSCALEFACTORRECOVEREDIN11AND16WAS20AND18,RESPECTIVELYINPARTICULAR,THEPROPOSEDALGORITHMDOESNOTRESULTTOINTERPOLATIONINEITHERSPATIALORFOURIERDOMAINONLY1DFFTOPERATIONSAREUSED,MAKINGITMUCHFASTERANDESPECIALLYSUITEDFORREALTIMEAPPLICATIONSTHERESTOFPAPERISORGANIZEDASFOLLOWSPRIORRESULTSRELATEDTOFFTBASEDIMAGEREGISTRATIONAREGIVENINSECTION2,WHILETHEPROPOSEDALGORITHM,ISPRESENTEDINSECTION3EXPERIMENTALRESULTSAREDISCUSSEDINSECTION4ANDFINALCONCLUSIONSAREGIVENINSECTION52PREVIOUSRELATEDWORK21TRANSLATIONESTIMATIONTHEBASISOFTHEFOURIERBASEDMOTIONESTIMATIONISTHESHIFTPROPERTY18OFTHEFOURIERTRANSFORMDENOTEBYFFFX,YG,BFΩX,ΩY1THEFOURIERTRANSFORMOFFX,YTHEN,FFFX￠X,Y￠YGBFΩX,ΩYEJΩX￠XΩY￠Y2EQUATION2CANBEUSEDFORTHEESTIMATIONOFIMAGETRANSLATION6,10ASSUMETHEIMAGESI1X,YANDI2X,YHAVESOMEOVERLAPTHATI1X￠X,Y￠YI2X,Y3PROCEEDINGSOFTHEIEEEWORKSHOPONMOTIONANDVIDEOCOMPUTINGWACV/MOTION’050769522718/052000IEEEROTATIONANDTRANSLATIONESTIMATIONALGORITHMOPERATESASFOLLOWS1LETM1,L1ANDM2,L2BETHESIZESOFI1I,JANDI2I,J,RESPECTIVELYTHEN,ATITERATIONN0,I1I,JANDI2I,JAREZEROPADDEDSUCHTHATM1L1M2L22K,K2Z122THEMAGNITUDESMPP1?ΘI,RJ￠ANDMPP2?ΘI,RJ￠OFTHEPPFFTSOFIN1I,JANDI2I,JARECALCULATED,RESPECTIVELY3THEPOLARDFTS,MAGNITUDESCMPOLAR1?ΘI,RJ￠ANDCMPOLAR2?ΘI,RJ￠OFIN1I,JANDI2I,JARESUBSTITUTEDBYMPP1?ΘI,RJ￠ANDMPP2?ΘI,RJ￠RESPECTIVELY4THETRANSLATIONALONGTHE?ΘAXISOFMPP1?ΘI,RJ￠ANDMPP2?ΘI,RJ￠ISESTIMATEDUSINGPHASECORRELATIONTHERESULTISDENOTEDBY￠ΘN5LETΘNBETHEACCUMULATEDROTATIONANGLEESTIMATEDATITERATIONNΘN,NXI0￠ΘIΘN?1￠ΘNTHEN,THEINPUTIMAGEI1I,JISROTATEDBYΘNAROUNDTHECENTEROFTHEIMAGEUSINGTHEFFTBASEDIMAGEROTATIONALGORITHMDESCRIBEDIN4THISROTATIONSCHEMEISACCURATEANDFASTSINCEONLY1DFFTOPERATIONSAREUSEDIN11Θ,RI01ΘΘN,R,N1,THEROTATIONCANBECONDUCTEDAROUNDANYPIXELWERECOMMENDTOUSETHECENTRALPIXELOFI1I,JSUCHTHATTHEBOUNDINGRECTANGULAROFTHEROTATEDIMAGEWILLBEASSMALLASPOSSIBLE6STEPS25AREREITERATEDUNTILTHEANGULARREFINEMENTTERM￠ΘNISSMALLERTHANAPREDEFINEDTHRESHOLDΕΘ,IEJ￠ΘNJ0THEPOLARAXISISAPPROXIMATEDUSINGTHESAMEPROCEDUREASINSECTION31,WHILETHERADIALAXISISAPPROXIMATEDUSINGNEARESTNEIGHBORINTERPOLATION4THERELATIVETRANSLATIONBETWEENCMLOG?POLAR1I,JANDCMLOG?POLAR2I,JISRECOVEREDBYA2DPHASECORRELATIONONTHE?ΘAND?RAXES5LET￠ΘNAND￠RNBETHEROTATIONANGLEANDTHESCALINGVALUEESTIMATEDATITERATIONN,RESPECTIVELYTHEN,THEINPUTIMAGEI1X,YISROTATEDAROUNDTHECENTEROFTHEIMAGE4ANDTHENSCALEDUSINGDFTDOMAINZEROPADDINGIN11Θ,RI01ΘΘN,R￠RN16WHEREΘNNXI0￠ΘIΘN?1￠ΘNRNNYI0￠RIRN?1￠￠RN17PROCEEDINGSOFTHEIEEEWORKSHOPONMOTIONANDVIDEOCOMPUTINGWACV/MOTION’050769522718/052000IEEE

簡介：LEARNINGMULTIROBOTJOINTACTIONPLANSFROMSIMULTANEOUSTASKEXECUTIONDEMONSTRATIONSMURILOFERNANDESMARTINSDEPTOFELECANDELECTRONICENGINEERINGIMPERIALCOLLEGELONDONLONDON,UKMURILOIEEEORGYIANNISDEMIRISDEPTOFELECANDELECTRONICENGINEERINGIMPERIALCOLLEGELONDONLONDON,UKYDEMIRISIMPERIALACUKABSTRACTTHECENTRALPROBLEMOFDESIGNINGINTELLIGENTROBOTSYSTEMSWHICHLEARNBYDEMONSTRATIONSOFDESIREDBEHAVIOURHASBEENLARGELYSTUDIEDWITHINTHEFIELDOFROBOTICSNUMEROUSARCHITECTURESFORACTIONRECOGNITIONANDPREDICTIONOFINTENTOFASINGLETEACHERHAVEBEENPROPOSEDHOWEVER,LITTLEWORKHASBEENDONEADDRESSINGHOWAGROUPOFROBOTSCANLEARNBYSIMULTANEOUSDEMONSTRATIONSOFMULTIPLETEACHERSTHISPAPERCONTRIBUTESANOVELAPPROACHFORLEARNINGMULTIROBOTJOINTACTIONPLANSFROMUNLABELLEDDATATHEROBOTSFIRSTLYLEARNTHEDEMONSTRATEDSEQUENCEOFINDIVIDUALACTIONSUSINGTHEHAMMERARCHITECTURESUBSEQUENTLY,THEGROUPBEHAVIOURISSEGMENTEDOVERTIMEANDSPACEBYAPPLYINGASPATIOTEMPORALCLUSTERINGALGORITHMTHEEXPERIMENTALRESULTS,INWHICHHUMANSTELEOPERATEDREALROBOTSDURINGASEARCHANDRESCUETASKDEPLOYMENT,SUCCESSFULLYDEMONSTRATEDTHEEFFICACYOFCOMBININGACTIONRECOGNITIONATINDIVIDUALLEVELWITHGROUPBEHAVIOURSEGMENTATION,SPOTTINGTHEEXACTMOMENTWHENROBOTSMUSTFORMCOALITIONSTOACHIEVETHEGOAL,THUSYIELDINGREASONABLEGENERATIONOFMULTIROBOTJOINTACTIONPLANSCATEGORIESANDSUBJECTDESCRIPTORSI29ARTIFICIALINTELLIGENCEROBOTICSGENERALTERMSALGORITHMS,DESIGN,EXPERIMENTATIONKEYWORDSLEARNINGBYDEMONSTRATION,MULTIROBOTSYSTEMS,SPECTRALCLUSTERING1INTRODUCTIONASUBSTANTIALAMOUNTOFSTUDIESINMULTIROBOTSYSTEMSMRSADDRESSESTHEPOTENTIALAPPLICATIONSOFENGAGINGMULTIPLEROBOTSTOCOLLABORATIVELYDEPLOYCOMPLEXTASKSSUCHASSEARCHANDRESCUE,DISTRIBUTEDMAPPINGANDEXPLORATIONOFUNKNOWNENVIRONMENTS,ASWELLASHAZARDOUSTASKSANDFORAGING–FORANOVERVIEWOFTHEFIELD,SEE13DESIGNINGDISTRIBUTEDINTELLIGENTSYSTEMS,SUCHASMRS,ISAPROFITABLECITEASLEARNINGMULTIROBOTJOINTACTIONPLANSFROMSIMULTANEOUSTASKEXECUTIONDEMONSTRATIONS,MFMARTINS,YDEMIRIS,PROCOF9THINTCONFONAUTONOMOUSAGENTSANDMULTIAGENTSYSTEMSAAMAS2010,VANDERHOEK,KAMINKA,LESPéRANCE,LUCKANDSENEDS,MAY,10–14,2010,TORONTO,CANADA,PP?COPYRIGHTC?2010,INTERNATIONALFOUNDATIONFORAUTONOMOUSAGENTSANDMULTIAGENTSYSTEMSWWWIFAAMASORGALLRIGHTSRESERVEDFIGURE1THEP3ATMOBILEROBOTSUSEDINTHISPAPER,EQUIPPEDWITHONBOARDCOMPUTERS,CAMERAS,LASERANDSONARRANGESENSORSTECHNOLOGYWHICHBRINGSBENEFITSSUCHASFLEXIBILITY,REDUNDANCYANDROBUSTNESS,AMONGOTHERSSIMILARLY,ASUBSTANTIALAMOUNTOFSTUDIESHAVEPROPOSEDNUMEROUSAPPROACHESTOROBOTLEARNINGBYDEMONSTRATIONLBD–FORACOMPREHENSIVEREVIEW,SEE1EQUIPPINGROBOTSWITHTHEABILITYTOUNDERSTANDTHECONTEXTINWHICHTHEYINTERACTWITHOUTTHENEEDOFCONFIGURINGORPROGRAMMINGTHEROBOTSISANEXTREMELYDESIREDFEATUREREGARDINGLBD,THEMETHODSWHICHHAVEBEENPROPOSEDAREMOSTLYFOCUSSEDONASINGLETEACHER,SINGLEROBOTSCENARIOIN7,ASINGLEROBOTLEARNTASEQUENCEOFACTIONSDEMONSTRATEDBYASINGLETEACHERIN12,THEAUTHORSPRESENTEDANAPPROACHWHEREAHUMANACTEDBOTHASATEACHERANDCOLLABORATORTOAROBOTTHEROBOTWASABLETOMATCHTHEPREDICTEDRESULTANTSTATEOFTHEHUMAN’SMOVEMENTSTOTHEOBSERVEDSTATEOFTHEENVIRONMENTBASEDONITSUNDERLYINGCAPABILITIESASUPERVISEDLEARNINGMETHODWASPRESENTEDIN4USINGGAUSSIANMIXTUREMODELS,INWHICHAFOURLEGGEDROBOTWASTELEOPERATEDDURINGANAVIGATIONTASKFEWSTUDIESADDRESSEDTHEPREDICTIONOFINTENTINADVERSARIALMULTIAGENTSCENARIOS,SUCHASTHEWORKOF3,INWHICHGROUPMANOEUVRESCOULDBEPREDICTEDBASEDUPONEXISTINGMODELSOFGROUPFORMATIONINTHEWORKOF5,MULTIPLEHUMANOIDROBOTSREQUESTEDATEACHER’SDEMONSTRATIONWHENFACINGUNFAMILIARSTATESIN14,THEPROBLEMOFEXTRACTINGGROUPBEHAVIOURFROMOBSERVEDCOORDINATEDMANOEUVRESOFMULTIPLEAGENTSALONGTIMEWASADDRESSEDBYUSINGACLUSTERINGALGORITHMTHEMETHODPRESENTEDIN9ALLOWEDASINGLEROBOTTOPREDICTTHEINTENTIONSOF2HUMANSBASEDONSPATIOTEMPORALRELATIONSHIPSHOWEVER,THECHALLENGEOFDESIGNINGANMRSSYSTEMINWHICHMULTIPLEROBOTSLEARNGROUPBEHAVIOURBYOBSERVATION931931938I1I2INF1F2FNSTATESATTM1M2MNPREDICTIONVERIFICATIONATT1PREDICTIONVERIFICATIONATT1PREDICTIONVERIFICATIONATT1P1P2PNFIGURE3DIAGRAMATICSTATEMENTOFTHEHAMMERARCHITECTUREBASEDONSTATEST,MULTIPLEINVERSEMODELSI1TOINCOMPUTEMOTORCOMMANDSM1TOMN,WITHWHICHTHECORRESPONDINGFORWARDMODELSF1TOFNFORMPREDICTIONSREGARDINGTHENEXTSTATEST1P1TOPNWHICHAREVERIFIEDATST1MAYPERFORMCERTAINACTIONSSEQUENTIALLYORSIMULTANEOUSLYRESULTINGINACOMBINATIONOFACTIONS,WHILETHEROBOTHASACCESSTOTHEJOYSTICKCOMMANDSONLYINORDERTORECOGNISEACTIONSFROMOBSERVEDDATAANDMANOEUVRECOMMANDS,THISPAPERMAKESUSEOFTHEHIERARCHICALATTENTIVEMULTIPLEMODELSFOREXECUTIONANDRECOGNITIONHAMMERARCHITECTURE7,WHICHHASBEENPROVENTOWORKVERYWELLWHENAPPLIEDTODISTINCTROBOTSCENARIOSHAMMERISBASEDUPONTHECONCEPTSOFMULTIPLEHIERARCHICALLYCONNECTEDINVERSEFORWARDMODELSINTHISARCHITECTURE,ANINVERSEMODELHASASINPUTSTHEOBSERVEDSTATEOFTHEENVIRONMENTANDTHETARGETGOALS,ANDITSOUTPUTSARETHEMOTORCOMMANDSREQUIREDTOACHIEVEORMAINTAINTHETARGETGOALSONTHEOTHERHAND,FORWARDMODELSHAVEASINPUTSTHEOBSERVEDSTATEANDMOTORCOMMANDS,ANDTHEOUTPUTISAPREDICTIONOFTHENEXTSTATEOFTHEENVIRONMENTASILLUSTRATEDINFIG3,EACHINVERSEFORWARDPAIRRESULTSINAHYPOTHESISBYSIMULATINGTHEEXECUTIONOFAPRIMITIVEBEHAVIOUR,ANDTHENTHEPREDICTEDSTATEISCOMPAREDTOTHEOBSERVEDSTATETOCOMPUTEACONFIDENCEVALUETHISVALUEREPRESENTSHOWCORRECT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簡介：556IEEETRANSACTIONSONCONTROLSYSTEMSTECHNOLOGY,VOL10,NO4,JULY2002LINEOFSIGHTRATEESTIMATIONANDLINEARIZINGCONTROLOFANIMAGINGSEEKERINATACTICALMISSILEGUIDEDBYPROPORTIONALNAVIGATIONJACQUESWALDMANN,MEMBER,IEEEABSTRACTACCELERATIONCOMMANDSINMISSILESGUIDEDBYPROPORTIONALNAVIGATIONREQUIRETHEMEASUREMENTOFLINEOFSIGHTLOSRATEITISOFTENOBTAINEDBYFILTERINGTHEOUTPUTOFATWODEGREEOFFREEDOM2DOFRATEGYROMOUNTEDONTHEINNERGIMBALOFTHESEEKERTHISPAPERDESCRIBESTHEMODELINGOFANIMAGINGSEEKERANDTHEFORMULATIONOFANEXTENDEDKALMANFILTEREKFFORTHEESTIMATIONOFLOSRATEFROMMEASUREMENTSOFRELATIVEANGULARDISPLACEMENTBETWEENSEEKERGIMBALSANDALOWCOSTSTRAPDOWNINERTIALUNITTHEAPPROACHAIMSATCIRCUMVENTINGTHENEEDFORTHERATEGYROONTHESEEKERALINEARIZINGFEEDBACKCONTROLLAWFORDECOUPLINGMISSILEMOTIONFROMTHATOFTHESEEKERISPROPOSEDBASEDONTHEFILTERMODELANDITSESTIMATESADDITIONALLY,THECONTROLLAWUSESVISUALINFORMATIONFROMTHEIMAGESEQUENCEFORTARGETTRACKINGSEEKERDYNAMICSANDCONTROLARETHENINTEGRATEDINTOADYNAMICMODELOFACRUCIFORMMISSILEEQUIPPEDWITHCANARDSANDROLLERONSANDGUIDEDBYPROPORTIONALNAVIGATIONINTHREEDIMENSIONAL3DINTERCEPTIONTASKSMONTECARLOSIMULATIONISEMPLOYEDTOEVALUATETHEOVERALLSYSTEMACCURACYSUBJECTTODIFFERENTINITIALCONDITIONSLATERALANDHEADONENGAGEMENTSANDTHEIMPACTOFROLLINGMOTIONDURINGHIGHMANEUVERSONMISSDISTANCETHEVALIDATIONMODELINCLUDESNOISEINTHEVARIOUSSENSORS,COUPLEDINERTIAOFTHESEEKERGIMBALS,SIGNALSATURATIONATVARIOUSSUBSYSTEMS,OPTICALGEOMETRICDISTORTION,ANDTARGETSEGMENTATIONERRORSINTHEIMAGEPLANEINITIALENGAGEMENTGEOMETRYANDROLLRATEDAMPINGATHIGHINCIDENCEANGLESHAVEBEENOBSERVEDTOHAVEASIGNIFICANTIMPACTONMISSDISTANCEINDEXTERMSIMAGESEQUENCEANALYSIS,KALMANFILTERING,MACHINEVISION,MISSILEGUIDANCE,NONLINEARESTIMATIONANDCONTROL,OPTICALDISTORTION,POINTINGSYSTEMSIINTRODUCTIONGIMBALLEDSEEKERSAREOFTENUTILIZEDINCONTEMPORARYTACTICALMISSILESTHEYSHOULDPROVIDERAPIDANDACCURATETRACKINGOFBORESIGHTERRORSIGNALSGENERATEDBYTHETARGETDETECTORLOCATEDINTHEINNERGIMBALTHEDEMANDSONSEEKERCONTROLBECOMEMORESEVEREATTHEENDGAMEPORTIONOFTHEENGAGEMENTINADEQUATEPERFORMANCERESULTSINLARGEMISSDISTANCESANDTHUSREDUCESTHEPROBABILITYOFASUCCESSFULINTERCEPTIONATWODEGREEOFFREEDOM2DOFRATEGYROISUSUALLYMOUNTEDONTHEINNERGIMBALANDFEEDSINERTIALANGULARRATEDIRECTLYTOTHETORQUERSTOPROVIDEBORESIGHTERRORTRACKINGANDSTABILIZATIONAGAINSTBASEMOTION1,2THELATTERISACONSEQUENCEMANUSCRIPTRECEIVEDDECEMBER11,2000REVISEDNOVEMBER9,2001MANUSCRIPTRECEIVEDINFINALFORMFEBRUARY22,2002RECOMMENDEDBYASSOCIATEEDITORSBANDATHEAUTHORISWITHTHECENTROTéCNICOAEROESPACIAL,INSTITUTOTECNOLóGICODEAERONáUTICA,DEPARTMENTOFSYSTEMSANDCONTROL,12228900S?OJOSéDOSCAMPOSSP,BRAZILEMAILJACQUESELEITACTABRPUBLISHERITEMIDENTIFIERS1063653602053563OFTHEMISSILEANGULARANDLINEARMOTIONDURINGTHEENGAGEMENTANDISTRANSMITTEDTOTHEGIMBALSBYMECHANICALMEANSACCURATESTABILIZATIONOFIMAGINGSEEKERSISCRITICALTOREDUCEIMAGESMEARINGWHICHINTURNIMPACTSADEQUATETARGETACQUISITION,SEGMENTATION,ANDTRACKINGADDITIONALLY,MINORMASSUNBALANCESADDTOTHEDISTURBANCESACTINGUPONTHEGIMBALSASTHEMISSILESUFFERSACCELERATIONSTHEPACKAGINGOFSUBSYSTEMSINTACTICALMISSILESISSERIOUSLYAFFECTEDBYVOLUMEANDAERODYNAMICCONSTRAINTSTHATULTIMATELYDICTATEMANEUVERABILITYGIMBALLEDSEEKERSAREUSUALLYPOSITIONEDATTHEFRONTTIPOFTHEMISSILENOTRARELYTHESIZEOFTHESEEKERANDITSSUPPORTINGSYSTEMSDICTATESTHESHAPEOFTHEFRONTTIPOFTHEMISSILEINSUCHCASES,THEBULKIERTHESHAPE,THEMOREINTENSEBECOMETHEGENERATEDSHOCKWAVESWHICHDEGRADEMISSILEPERFORMANCESEEKERVOLUMECANBEREDUCEDBYREMOVINGTHERATEGYROFROMTHEGIMBALLEDASSEMBLYANDUSINGASTRAPDOWNCONFIGURATIONHOWEVER,THEAPPROACHCALLSFORTHEESTIMATIONOFTHEINNERGIMBALANGULARRATERELATIVETOTHEMISSILEBODYDIFFERENTIATIONOFTHERELATIVEANGULARRATEOFTHEGIMBALSANDFURTHERMATCHEDFILTERINGTOREDUCENOISEHASBEENUSEDINALINEARIZEDAPPROACH3TOSTABILIZEASINGLEAXISGIMBALLEDIMAGINGSEEKERDISTURBEDBYMISSILEMOTIONINCORRECTOUTPUTBYTHEIMAGESEGMENTATIONALGORITHMWASNEGLECTEDSLIDINGMODECONTROLHASBEENUSED4UNDERTHEASSUMPTIONOFUNCOUPLEDIDENTICALPITCHANDYAWCHANNELSAGAINWITHASINGLEAXISGIMBALLEDSEEKERANDEVALUATEDAGAINSTAREPRESENTATIVECOMMANDSIGNALTHEPROPOSEDCONTROLLAWREQUIREDTHECOMPUTATIONOFFIRSTANDSECONDTIMEDERIVATIVESOFTHECOMMANDSIGNALASWELLASPERFECTMEASUREMENTSOFGIMBALANGULARDISPLACEMENTANDRATERELATIVETOTHEMISSILEBODYTHISPAPERPROPOSESTOEXTENDTHEABOVEFORMULATIONTOCOPEWITHTHEDYNAMICSOFAYAWANDPITCHCONTROLLEDIMAGINGSEEKERTHEAPPROACHISBASEDONMODELINGTHENONLINEARSEEKERDYNAMICSWITHITSTIMEVARYINGINERTIAFORUSEINANEXTENDEDKALMANFILTEREKF,AIMINGATTHEESTIMATIONOFRELATIVEANGULARDISPLACEMENTOFTHEGIMBALSFURTHERMORE,IMAGESEQUENCEANALYSISASSUMINGTHATTARGETSEGMENTATIONHASBEENSOLVEDANDANOISYESTIMATEOFITSCENTROIDLOCATIONINTHEIMAGEPLANEISAVAILABLEISADDRESSEDINTERMSOFOPTICALFLOW21ESTIMATIONFORVISUALFEEDBACKTOTHETORQUERSTHEAPPROACHISEVALUATEDBYASSESSINGTHEMISSDISTANCESTATISTICSVIAMONTECARLOSIMULATIONOFTHECLOSEDLOOPCOMPRISINGSEEKERCONTROLANDTHEDYNAMICMODELOFATACTICALCRUCIFORMMISSILETHEMISSILEISGUIDEDBYPUREPROPORTIONALNAVIGATIONINTHREEDIMENSIONAL3DENGAGEMENTSAGAINSTONENONMANEUVERINGTARGET10636536/021700?2002IEEE558IEEETRANSACTIONSONCONTROLSYSTEMSTECHNOLOGY,VOL10,NO4,JULY2002DYNAMICSOFTHELASTTWOCOMPONENTSIN1BWHENEXCITEDBYTORQUEFROMTHEACTUATORSTHEFIRSTCOMPONENTREFERSTOTHEREACTIONTORQUEOFTHEMISSILEBODYACTINGUPONTHEOUTERGIMBALANDHENCEISNOTCONSIDEREDINTHEENSUINGMODELONONEHAND,TORQUECOMPONENTISAPPLIEDTOTHEOUTERGIMBALALONGTHEDIRECTIONANDAFFECTSTHEANGULARMOMENTUMCOMPONENTOFBOTHGIMBALSGIVENBYTORQUECOMPONENT,ONTHEOTHERHAND,ISAPPLIEDTOTHEINNERGIMBALALONGTHEDIRECTIONBYANACTUATORLOCATEDINSUCHWAYATTHEOUTERGIMBALTHATITSACTIONISPERPENDICULARTOTHEREFORE,ONLYAFFECTSTHEANGULARMOMENTUMCOMPONENTOFTHEINNERGIMBALALONGDIRECTION,GIVENBY4SUBSTITUTING2–4IN1BPRODUCESTHEFOLLOWING5A5BWHICHYIELDSAFTERSOMEALGEBRAICMANIPULATION6A6B6C6D6E6F6G6H6I6J6KTHEDYNAMICMODELOFSEEKERMOTIONRELATIVETOTHENBECOMES7AAND7BATTHEBOTTOMOFTHEPAGEANDTHEDYNAMICCOUPLINGARISINGFROMTHEINERTIAPRODUCTSBECOMESAPPARENTTORQUERDYNAMICSISMODELEDBY8WHERE,ARECURRENTSIGNALSAPPLIEDTOEACHTORQUERAND,ARECONSTANTGAINSTHECURRENTSIGNALSTOTHETORQUERSMUSTDRIVETHESEEKER,AIMINGATBASEMOTIONSTABILIZATIONANDTARGETTRACKINGINERTIAMOMENTSANDPRODUCTSOFBOTHGIMBALSANDELECTROOPTICALPAYLOADAREKNOWNALONGTORQUERAXESPRIORTOSEEKERASSEMBLYTHETORQUERAXESAREALIGNEDWITHTHECOORDINATEFRAMETHEREFORE,THEINERTIAPARAMETERSOFTHEINNERGIMBALASSEMBLYANDITSPAYLOADRELATIVETOTHEFRAMEVARYINTIMEDURINGSEEKEROPERATIONDUETOTHEOCCURRENCEOFRELATIVEMOTIONINELEVATION,GIVENBYANDTHEINERTIAMOMENTSANDPRODUCTSOFTHEINNERGIMBALANDELECTROOPTICALPAYLOADINTHEFRAME,ALONGWITHTHERESPECTIVETIMERATES,ARECOMPUTEDAS9EQUATIONS6–9COMPOSETHEDYNAMICMODELRELATINGTHEINPUTDRIVINGTHETORQUERSTOTHEOUTPUT,WHICHISTHESEEKERMOTIONRELATIVETOTHECOORDINATEFRAMEINORDERTOSTABILIZETHESEEKERININERTIALSPACEANDTRACKTHETARGETWHILEPERFORMINGPROPORTIONALNAVIGATION,THEINERTIALLOSRATEFROMSEEKERTOTARGETHASTOBEESTIMATEDFROMAVAILABLEMISSILEANGULARRATEANDRELATIVEGIMBALANGLEMEASUREMENTSINORDERTOCIRCUMVENTTHENEEDFORA2DOFRATEGYROMOUNTEDONTHEINNERGIMBALSECTIONIIIDESCRIBESTHEFORMULATIONOFANEKFFORTHISPURPOSEIIILOSRATEESTIMATIONVIAEKFTHEAVAILABLEMEASUREMENTSFORLOSRATEESTIMATIONARETHEOUTERGIMBALANGLERELATIVETOTHEMISSILEBODY,INNERGIMBAL7A7B

簡介：從同步任務(wù)執(zhí)行演示中學(xué)習(xí)多個機(jī)器人聯(lián)合行動計劃從同步任務(wù)執(zhí)行演示中學(xué)習(xí)多個機(jī)器人聯(lián)合行動計劃MURILOIEEEORGMURILOIEEEORGELECELEC與電子工程系，穆里羅費(fèi)爾南德斯馬丁斯，英國倫敦帝國學(xué)倫敦，英與電子工程系，穆里羅費(fèi)爾南德斯馬丁斯，英國倫敦帝國學(xué)倫敦，英國摘要摘要設(shè)計智能機(jī)器人通過行為示范已經(jīng)很大程度上影響了機(jī)器人系統(tǒng)的核心。許多架構(gòu)的認(rèn)識和預(yù)測提出了一個教師的意圖。無論如何，很少的工作被完成訪問如何使一組機(jī)器人能夠在許多教師同時地示范中學(xué)習(xí)。本文有助于學(xué)習(xí)多個機(jī)器人聯(lián)合行動計劃不存在的數(shù)據(jù)。個人行為的機(jī)器人首先學(xué)習(xí)錘子架構(gòu)，隨后,運(yùn)用時空聚類算法將行為分割在時間和空間上。根據(jù)實驗結(jié)果表明，人類遠(yuǎn)程操作機(jī)器人在搜索和營救任務(wù)布置旗艦成功的示范了個人水平結(jié)合性行為識別和團(tuán)體行為分割的功效，測定準(zhǔn)確的時刻和讓機(jī)器人必須聯(lián)合實現(xiàn)預(yù)期的目標(biāo)，因此生產(chǎn)一代合理的多功能機(jī)器人聯(lián)合行動計劃。分類和主題描述符號【人造的智力】機(jī)器人概述算法，設(shè)計，實驗關(guān)鍵詞關(guān)鍵詞從示范中學(xué)習(xí)，多功能機(jī)器人系統(tǒng)，光譜的采集11引言引言對多功能機(jī)器人系統(tǒng)研究的本質(zhì)發(fā)表演說，潛在的應(yīng)用程序保證大多數(shù)機(jī)器人能合作地部署復(fù)雜的任務(wù)，像搜索和營救。分配地圖和探索陌生的環(huán)境，有危險的任務(wù)和覓食一樣對于領(lǐng)域的一個綜述，看【13】，設(shè)計分散式的智能系統(tǒng)，比如，MPS，是賺錢的科技，他帶來的益處比如靈活性，裁員和穩(wěn)健性。本節(jié)還介紹錘架構(gòu)7和14提出的SC算法的實現(xiàn)是如何被利用來解決動作識別和群體行為的分割問題，其次，在第4部分描述了正是多功能機(jī)器人計劃的產(chǎn)生實驗性的測試已完成，第5部分分析得到的結(jié)果，最后，第6部分給出了結(jié)論和進(jìn)一步的工作。2系統(tǒng)設(shè)計問題這篇文章的MOLBD體系結(jié)構(gòu)計劃是基于機(jī)器人遙控平臺，被【8】和【16】的工作所啟迪的設(shè)計，還有LBD體系結(jié)構(gòu)在【7】【9】所呈現(xiàn)的。一些MRS的設(shè)計包括了在這個研究區(qū)域的普遍問題，尤其是機(jī)器人遙控系統(tǒng)帶來了幾個核心的（重要的）設(shè)計問題，在接下來的章節(jié)會論述到。21人類VS機(jī)器人感知中心遙控平臺通常提供在機(jī)器人附著的遠(yuǎn)程環(huán)境中受限制的直覺，然而，依賴于應(yīng)用和環(huán)境，人類可以以全面的。不受限制的觀察的這樣一種方式戰(zhàn)略性地被安置是可行的。第一被說明的設(shè)計問題是人類VS機(jī)器人幾種的知覺人被允許觀察自己的感覺世界或者他們應(yīng)該有自己的看法僅限于機(jī)器人介導(dǎo)的數(shù)據(jù)。。但先前的表現(xiàn)導(dǎo)致了簡化的系統(tǒng)，上述的MRS潛在運(yùn)用難免會落后，執(zhí)行這項工作的遙控平臺因此基于對環(huán)境的受限制的知覺，為人類提空了機(jī)器人可以通過他的傳感器獲得的本地的相同的遙遠(yuǎn)的知覺（人類被放置在機(jī)器人有知覺的鞋里）。22人類行為的觀察設(shè)計一個遙控操作平臺的另一個關(guān)鍵問題是如何定義相關(guān)的命令發(fā)送給機(jī)器人。人類的行為是不能被機(jī)器人直接觀察到的。盡管人類是“放置在機(jī)器人的感知中心一個機(jī)器人只能訪問它的遙控機(jī)器人的動作指令，而不是人類的動作一圖。如圖2所示。

簡介：三維空間攔截的前置追蹤變結(jié)構(gòu)制導(dǎo)律三維空間攔截的前置追蹤變結(jié)構(gòu)制導(dǎo)律葛連正,沈毅,高云峰,趙立軍哈爾濱工業(yè)大學(xué)控制科學(xué)與工程系，黑龍江哈爾濱150001摘要摘要為了解決導(dǎo)引頭探測由于高速運(yùn)動所引起的干擾問題，提出了空間攔截的前置攔截方式。在建立了前置追蹤導(dǎo)引方式的三維制導(dǎo)模型的基礎(chǔ)上，對機(jī)動目標(biāo)攔截基于李亞普諾夫穩(wěn)定性分析方法設(shè)計了一種前置追蹤非線性變結(jié)構(gòu)制導(dǎo)律。前置追蹤制導(dǎo)律將攔截器導(dǎo)引到目標(biāo)軌道的前方進(jìn)行攔截，要求攔截器的速度小于目標(biāo)導(dǎo)彈的速度。攔截器和目標(biāo)導(dǎo)彈彈道攔截的三維數(shù)字仿真驗證了制導(dǎo)模型和制導(dǎo)律的正確性。關(guān)鍵詞前置追蹤；三維制導(dǎo)模型；非線性變結(jié)構(gòu)；李亞普諾夫定理；制導(dǎo)律1引言引言在攔截戰(zhàn)術(shù)彈道導(dǎo)彈的攔截，多用來探測目標(biāo)的紅外導(dǎo)引頭。然而，檢測精度往往是由于氣動加熱而退化1。為了解決氣動燒蝕問題，最近已開發(fā)的前置追蹤（HP）制導(dǎo)律攔截導(dǎo)彈，它的位置在對其飛行軌跡的目標(biāo)摧毀目標(biāo)2。利用該制導(dǎo)律，攔截器可以飛相同的方向與目標(biāo)在一個較低的速度擊中目標(biāo)。相比于正面接觸，低速度達(dá)到減少能源消耗。HP的指導(dǎo)方法是文獻(xiàn)中的進(jìn)一步改進(jìn)。相對運(yùn)動模型可以被視為兩個垂直通道和制導(dǎo)問題每一個平面的問題。前置追蹤變結(jié)構(gòu)制導(dǎo)律進(jìn)行了基于平面的模型。然而，由于實際導(dǎo)彈攔截發(fā)生在在三維空間中，一個三維的前置追蹤指導(dǎo)方法在實際中是比較有用的。各種經(jīng)典制導(dǎo)方法已檢查的三維制導(dǎo)攔截以來實施的三維純比例導(dǎo)引律由艾德勒提出的起源5。參考文獻(xiàn)611。已開發(fā)的三維制導(dǎo)模型，給出了基于李雅普諾夫穩(wěn)定性理論指導(dǎo)法。這些制導(dǎo)律只適宜迎面攔截，攔截方式和運(yùn)動學(xué)模型不同于HP的指導(dǎo)方法。作為一個直觀的強(qiáng)大的控制技術(shù)，滑模變結(jié)構(gòu)控制1215一直在用各種指導(dǎo)應(yīng)用用來解決大的建模誤差和不確定性的非線性1??Ω?2COSCOS?COSCOS?COSCOSSINCOSTANCOSSIN?COSSIN??3COSSIN?COSSIN?COS?SINSINSIN?SIN?4SINTANCOSSIN?COSSIN?COSSIN?SIN?COSCOSSINCOSTAN?COSSIN?COSSIN??5COSSIN?COSSIN?COSSINSINSIN?SIN?SINTANCOSSIN?COSSIN?COS6SIN?SIN和VT分別是攔截器速度矢量和目標(biāo)速度矢量。Ω1是LOS的視線角速度矢量。AYT和AZT分別是假定上的目標(biāo)機(jī)動加速度和偏航機(jī)動加速度。AYM和AZM分別是俯仰機(jī)動加速度和攔截器的偏航機(jī)動加速度。前置追蹤制導(dǎo)律要求攔截器的速度低于目標(biāo)，所以速度比定義為7N1為了達(dá)到目標(biāo)，在攔截點R0不僅是必需的，但也需要目標(biāo)在方向上攔截飛行器，因此,8LIM→00LIM→00,9LIM→00LIM→00指導(dǎo)法的目的是使前置追蹤的攔截器的達(dá)到這個點，這是限制的公式。（8）（9）。因此，攔截器導(dǎo)角ΘM和MΦ需要與目標(biāo)的鉛角度相對瞄準(zhǔn)線,1012

簡介：1一種尋的制導(dǎo)導(dǎo)彈模型參考變結(jié)構(gòu)自動駕駛儀的設(shè)計摘要設(shè)計某尋的導(dǎo)彈的自動駕駛儀回路,使導(dǎo)彈控制系統(tǒng)在正確響應(yīng)制導(dǎo)指令的同時,對彈體氣動力參數(shù)變化、量測噪聲等具有很好的抑制作用。將模型參考自適應(yīng)控制方法與變結(jié)構(gòu)控制方法相結(jié)合,為某型導(dǎo)彈設(shè)計了結(jié)構(gòu)簡單、實現(xiàn)方便的模型參考變結(jié)構(gòu)控制系統(tǒng)。仿真結(jié)構(gòu)表明,模型參考變結(jié)構(gòu)自動駕駛儀不僅能準(zhǔn)確傳遞制導(dǎo)指令,而且具有很好的魯棒性,能有效地抑制氣動力浮動、量測噪聲等干擾因素。關(guān)鍵詞模型參考變結(jié)構(gòu),變結(jié)構(gòu)控制,自動駕駛儀導(dǎo)彈控制系統(tǒng)的任務(wù)如下第一個是穩(wěn)定彈體，使彈體具有適當(dāng)?shù)淖枘?，第二個是要正確引導(dǎo)轉(zhuǎn)移命令使舵偏轉(zhuǎn)和改變其性能最終目標(biāo)是改變速度的大小和方向，并迫使導(dǎo)彈準(zhǔn)確命中目標(biāo)。然而，在導(dǎo)彈飛行期間，彈體的模型具有一定的不確定性，因為導(dǎo)彈的質(zhì)量，速度，和測量噪聲具有多樣性。此外，該導(dǎo)彈動力學(xué)在本質(zhì)上是高度非線性的。經(jīng)典控制理論和適應(yīng)性控制理論適合于線性發(fā)電站不能給出可靠的設(shè)計導(dǎo)彈自動駕駛儀?？勺兘Y(jié)構(gòu)控制系統(tǒng)理論在本質(zhì)上是一個控制理論的非線性系統(tǒng)，并且根據(jù)系統(tǒng)多樣性的現(xiàn)狀改變其結(jié)構(gòu)所以它能比常規(guī)的控制理論更有效的控制。此外可變結(jié)構(gòu)控制的滑動模式對于干擾更加穩(wěn)定，許多研究表明，可變結(jié)構(gòu)控制方法適用于導(dǎo)彈控制系統(tǒng)的設(shè)計。模型參考適應(yīng)性控制系統(tǒng)是一個很好的控制裝置，用于參數(shù)變化緩慢的線性發(fā)電站。自從控制發(fā)電廠和參考模型直接進(jìn)行比較，適應(yīng)的速度高，控制器可以很容易地實現(xiàn)，但該模型參考適應(yīng)性控制只適合連續(xù)系統(tǒng)的模型是可以肯定的，并可能當(dāng)在有干擾，噪音和未建模動態(tài)的時候有不穩(wěn)定的現(xiàn)象。本文為了自導(dǎo)引導(dǎo)彈結(jié)合了可變結(jié)構(gòu)控制的模型參考適應(yīng)性控制和設(shè)計MRVS的自動駕駛儀。1模型參考變結(jié)構(gòu)系統(tǒng)設(shè)計由于ROLL穩(wěn)定的導(dǎo)彈系統(tǒng)的特性本文僅討論導(dǎo)彈的單輸入系統(tǒng)。302222212121???????SBUUBBXAAXAAPMMMM（8）將UP變?yōu)橄旅娴男问?，即MMPUKXKXKEKEKU?????24132211不等式為????????????????????????????00}{0}{00242222212121312121111122222121112111SUBKUBBSXBKXAAACASXBKXAAACASEBKEACASEBKEACAMMMMMMMMMMM（9）然后不等式8將成立，即UP會滿足變結(jié)構(gòu)控制的達(dá)成條件。如果B0，然后當(dāng)K1,K2,K3,K4,KM得到以下值，即????????????????????????????????????SGNMAXSGNMAXSGNMAXSGNMAXSGNMAX2222121242121111132212221111SBBBKSBAAAACKSBAAAACKSBACAKSBACAKMMMMMMMMMM（10）公式（9）將全部成立。為了抑制震動，一個飽和函數(shù)將取代開環(huán)函數(shù)SGNS。2一些尋的導(dǎo)彈自動駕駛儀設(shè)計一般來說，彈體是弱阻尼，所以螺距角速率的反饋通常被用來增加阻尼反饋循環(huán)也可以使從引導(dǎo)命令的傳輸系數(shù)的對過載的變化越小越好。本文中使用的內(nèi)部循環(huán)作為發(fā)電站設(shè)計MRVS的自動駕駛儀。彈體的傳遞函數(shù)通常被表示為其中N是過載，也就是彈體的輸出，U為引導(dǎo)命令的電廠輸入。為了使用MRVS，電廠的傳遞函數(shù)被首先改變?yōu)闋顟B(tài)空間模型。導(dǎo)彈本身的傳遞函數(shù)通常表示為

簡介：INTJADVMANUFTECHNOL200016739–747?2000SPRINGERVERLAGLONDONLIMITEDAUTOMATEDASSEMBLYMODELLINGFORPLASTICINJECTIONMOULDSXGYE,JYHFUHANDKSLEEDEPARTMENTOFMECHANICALANDPRODUCTIONENGINEERING,NATIONALUNIVERSITYOFSINGAPORE,SINGAPOREANINJECTIONMOULDISAMECHANICALASSEMBLYTHATCONSISTSOFPRODUCTDEPENDENTPARTSANDPRODUCTINDEPENDENTPARTSTHISPAPERADDRESSESTHETWOKEYISSUESOFASSEMBLYMODELLINGFORINJECTIONMOULDS,NAMELY,REPRESENTINGANINJECTIONMOULDASSEMBLYINACOMPUTERANDDETERMININGTHEPOSITIONANDORIENTATIONOFAPRODUCTINDEPENDENTPARTINANASSEMBLYAFEATUREBASEDANDOBJECTORIENTEDREPRESENTATIONISPROPOSEDTOREPRESENTTHEHIERARCHICALASSEMBLYOFINJECTIONMOULDSTHISREPRESENTATIONREQUIRESANDPERMITSADESIGNERTOTHINKBEYONDTHEMERESHAPEOFAPARTANDSTATEEXPLICITLYWHATPORTIONSOFAPARTAREIMPORTANTANDWHYTHUS,ITPROVIDESANOPPORTUNITYFORDESIGNERSTODESIGNFORASSEMBLYDFAASIMPLIFIEDSYMBOLICGEOMETRICAPPROACHISALSOPRESENTEDTOINFERTHECONFIGURATIONSOFASSEMBLYOBJECTSINANASSEMBLYACCORDINGTOTHEMATINGCONDITIONSBASEDONTHEPROPOSEDREPRESENTATIONANDTHESIMPLIFIEDSYMBOLICGEOMETRICAPPROACH,AUTOMATICASSEMBLYMODELLINGISFURTHERDISCUSSEDKEYWORDSASSEMBLYMODELLINGFEATUREBASEDINJECTIONMOULDSOBJECTORIENTED1INTRODUCTIONINJECTIONMOULDINGISTHEMOSTIMPORTANTPROCESSFORMANUFACTURINGPLASTICMOULDEDPRODUCTSTHENECESSARYEQUIPMENTCONSISTSOFTWOMAINELEMENTS,THEINJECTIONMOULDINGMACHINEANDTHEINJECTIONMOULDTHEINJECTIONMOULDINGMACHINESUSEDTODAYARESOCALLEDUNIVERSALMACHINES,ONTOWHICHVARIOUSMOULDSFORPLASTICPARTSWITHDIFFERENTGEOMETRIESCANBEMOUNTED,WITHINCERTAINDIMENSIONLIMITS,BUTTHEINJECTIONMOULDDESIGNHASTOCHANGEWITHPLASTICPRODUCTSFORDIFFERENTMOULDINGGEOMETRIES,DIFFERENTMOULDCONFIGURATIONSAREUSUALLYNECESSARYTHEPRIMARYTASKOFANINJECTIONMOULDISTOSHAPETHEMOLTENMATERIALINTOTHEFINALSHAPEOFTHEPLASTICPRODUCTTHISTASKISFULFILLEDBYTHECAVITYSYSTEMTHATCONSISTSOFCORE,CAVITY,INSERTS,ANDSLIDER/LIFTERHEADSTHEGEOMETRICALSHAPESCORRESPONDENCEANDOFFPRINTREQUESTSTODRJERRYYHFUH,DEPARTMENTOFMECHANICALANDPRODUCTIONENGINEERING,NATIONALUNIVERSITYOFSINGAPORENUS,10KENTRIDGECRESCENT,SINGAPORE119260EMAILMPEFUHYH?NUSEDUSGANDSIZESOFACAVITYSYSTEMAREDETERMINEDDIRECTLYBYTHEPLASTICMOULDEDPRODUCT,SOALLCOMPONENTSOFACAVITYSYSTEMARECALLEDPRODUCTDEPENDENTPARTSHEREINAFTER,PRODUCTREFERSTOAPLASTICMOULDEDPRODUCT,PARTREFERSTOTHECOMPONENTOFANINJECTIONMOULDBESIDESTHEPRIMARYTASKOFSHAPINGTHEPRODUCT,ANINJECTIONMOULDHASALSOTOFULFILANUMBEROFTASKSSUCHASTHEDISTRIBUTIONOFMELT,COOLINGTHEMOLTENMATERIAL,EJECTIONOFTHEMOULDEDPRODUCT,TRANSMITTINGMOTION,GUIDING,ANDALIGNINGTHEMOULDHALVESTHEFUNCTIONALPARTSTOFULFILTHESETASKSAREUSUALLYSIMILARINSTRUCTUREANDGEOMETRICALSHAPEFORDIFFERENTINJECTIONMOULDSTHEIRSTRUCTURESANDGEOMETRICALSHAPESAREINDEPENDENTOFTHEPLASTICMOULDEDPRODUCTS,BUTTHEIRSIZESCANBECHANGEDACCORDINGTOTHEPLASTICPRODUCTSTHEREFORE,ITCANBECONCLUDEDTHATANINJECTIONMOULDISACTUALLYAMECHANICALASSEMBLYTHATCONSISTSOFPRODUCTDEPENDENTPARTSANDPRODUCTINDEPENDENTPARTSFIGURE1SHOWSTHEASSEMBLYSTRUCTUREOFANINJECTIONMOULDTHEDESIGNOFAPRODUCTDEPENDENTPARTISBASEDONEXTRACTINGTHEGEOMETRYFROMTHEPLASTICPRODUCTINRECENTYEARS,CAD/CAMTECHNOLOGYHASBEENSUCCESSFULLYUSEDTOHELPMOULDDESIGNERSTODESIGNTHEPRODUCTDEPENDENTPARTSTHE?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????FIG1ASSEMBLYSTRUCTUREOFANINJECTIONMOULDAUTOMATEDASSEMBLYMODELLING741BASEDONAUTOCAD,ITCOULDONLYACCOMMODATEWIREFRAMEANDSIMPLESOLIDMODELS3REPRESENTATIONOFINJECTIONMOULDASSEMBLIESTHETWOKEYISSUESOFAUTOMATEDASSEMBLYMODELLINGFORINJECTIONMOULDSARE,REPRESENTINGAMOULDASSEMBLYINCOMPUTERS,ANDDETERMININGTHEPOSITIONANDORIENTATIONOFAPRODUCTINDEPENDENTPARTINTHEASSEMBLYINTHISSECTION,WEPRESENTANOBJECTORIENTEDANDFEATUREBASEDREPRESENTATIONFORASSEMBLIESOFINJECTIONMOULDSTHEREPRESENTATIONOFASSEMBLIESINACOMPUTERINVOLVESSTRUCTURALANDSPATIALRELATIONSHIPSBETWEENINDIVIDUALPARTSSUCHAREPRESENTATIONMUSTSUPPORTTHECONSTRUCTIONOFANASSEMBLYFROMALLTHEGIVENPARTS,CHANGESINTHERELATIVEPOSITIONINGOFPARTS,ANDMANIPULATIONOFTHEASSEMBLYASAWHOLEMOREOVER,THEREPRESENTATIONSOFASSEMBLIESMUSTMEETTHEFOLLOWINGREQUIREMENTSFROMDESIGNERS1ITSHOULDBEPOSSIBLETOHAVEHIGHLEVELOBJECTSREADYTOUSEWHILEMOULDDESIGNERSTHINKONTHELEVELOFREALWORLDOBJECTS2THEREPRESENTATIONOFASSEMBLIESSHOULDENCAPSULATEOPERATIONALFUNCTIONSTOAUTOMATEROUTINEPROCESSESSUCHASPOCKETINGANDINTERFERENCECHECKSTOMEETTHESEREQUIREMENTS,AFEATUREBASEDANDOBJECTORIENTEDHIERARCHICALMODELISPROPOSEDTOREPRESENTINJECTIONMOULDSANASSEMBLYMAYBEDIVIDEDINTOSUBASSEMBLIES,WHICHINTURNCONSISTSOFSUBASSEMBLIESAND/ORINDIVIDUALCOMPONENTSTHUS,AHIERARCHICALMODELISMOSTAPPROPRIATEFORREPRESENTINGTHESTRUCTURALRELATIONSBETWEENCOMPONENTSAHIERARCHYIMPLIESADEFINITEASSEMBLYSEQUENCEINADDITION,AHIERARCHICALMODELCANPROVIDEANEXPLICITREPRESENTATIONOFTHEDEPENDENCYOFTHEPOSITIONOFONEPARTONANOTHERFEATUREBASEDDESIGN10ALLOWSDESIGNERSTOWORKATASOMEWHATHIGHERLEVELOFABSTRACTIONTHANTHATPOSSIBLEWITHTHEDIRECTUSEOFSOLIDMODELLERSGEOMETRICFEATURESAREINSTANCED,SIZED,ANDLOCATEDQUICKLYBYTHEUSERBYSPECIFYINGAMINIMUMSETOFPARAMETERS,WHILETHEFEATUREMODELLERWORKSOUTTHEDETAILSALSO,ITISEASYTOMAKEDESIGNCHANGESBECAUSEOFTHEASSOCIATIVITIESBETWEENGEOMETRICENTITIESMAINTAINEDINTHEDATASTRUCTUREOFFEATUREMODELLERSWITHOUTFEATURES,DESIGNERSHAVETOBECONCERNEDWITHALLTHEDETAILSOFGEOMETRICCONSTRUCTIONPROCEDURESREQUIREDBYSOLIDMODELLERS,ANDDESIGNCHANGESHAVETOBESTRICTLYSPECIFIEDFOREVERYENTITYAFFECTEDBYTHECHANGEMOREOVER,THEFEATUREBASEDREPRESENTATIONWILLPROVIDEHIGHLEVELASSEMBLYOBJECTSFORDESIGNERSTOUSEFOREXAMPLE,WHILEMOULDDESIGNERSTHINKONTHELEVELOFAREALWORLDOBJECT,EGACOUNTERBOREHOLE,AFEATUREOBJECTOFACOUNTERBOREHOLEWILLBEREADYINTHECOMPUTERFORUSEOBJECTORIENTEDMODELLING11,12ISANEWWAYOFTHINKINGABOUTPROBLEMSUSINGMODELSORGANISEDAROUNDREALWORLDCONCEPTSTHEFUNDAMENTALENTITYISTHEOBJECT,WHICHCOMBINESBOTHDATASTRUCTURESANDBEHAVIOURINASINGLEENTITYOBJECTORIENTEDMODELSAREUSEFULFORUNDERSTANDINGPROBLEMSANDDESIGNINGPROGRAMSANDDATABASESINADDITION,THEOBJECTORIENTEDREPRESENTATIONOFASSEMBLIESMAKESITEASYFORA“CHILD”O(jiān)BJECTTOINHERITINFORMATIONFROMITS“PARENT”FIGURE2SHOWSTHEFEATUREBASEDANDOBJECTORIENTEDHIERARCHICALREPRESENTATIONOFANINJECTIONMOULDTHEREPRESENTATIONISAHIERARCHICALSTRUCTUREATMULTIPLELEVELSOFABSTRACTION,FROMLOWLEVELGEOMETRICENTITIESFORMFEATURETOHIGHLEVELSUBASSEMBLIESTHEITEMSENCLOSEDINTHEBOXESREPRESENT“ASSEMBLYOBJECTS”SUBFAS,PARTSANDFFSTHESOLIDLINESREPRESENT“PARTOF”RELATIONANDTHEDASHEDLINESREPRESENTOTHERRELATIONSHIPSSUBASSEMBLYSUBFACONSISTSOFPARTSPARTSAPARTCANBETHOUGHTOFASAN“ASSEMBLY”O(jiān)FFORMFEATURESFFSTHEREPRESENTATIONCOMBINESTHESTRENGTHSOFAFEATUREBASEDGEOMETRICMODELWITHTHOSEOFOBJECTORIENTEDMODELSITNOTONLYCONTAINSTHE“PARTOF”RELATIONSBETWEENTHEPARENTOBJECTANDTHECHILDOBJECT,BUTALSOINCLUDESARICHERSETOFSTRUCTURALRELATIONSANDAGROUPOFOPERATIONALFUNCTIONSFORASSEMBLYOBJECTSINSECTION31,THEREISFURTHERDISCUSSIONONTHEDEFINITIONOFANASSEMBLYOBJECT,ANDDETAILEDRELATIONSBETWEENASSEMBLYOBJECTSAREPRESENTEDINSECTION3231DEFINITIONOFASSEMBLYOBJECTSINOURWORK,ANASSEMBLYOBJECT,O,ISDEFINEDASAUNIQUE,IDENTIFIABLEENTITYINTHEFOLLOWINGFORMOOID,A,M,R1WHEREOIDISAUNIQUEIDENTIFIEROFANASSEMBLYOBJECTOAISASETOFTHREETUPLES,T,A,VEACHAISCALLEDANATTRIBUTEOFO,ASSOCIATEDWITHEACHATTRIBUTEISATYPE,T,ANDAVALUE,VMISASETOFTUPLES,M,TC1,TC2,,TCN,TCEACHELEMENTOFMISAFUNCTIONTHATUNIQUELYIDENTIFIESAMETHODTHESYMBOLMREPRESENTSAMETHODNAMEANDMETHODSDEFINEOPERATIONSONOBJECTSTHESYMBOLTCIIFIG2FEATUREBASED,OBJECTORIENTEDHIERARCHICALREPRESENTATION

簡介：中文中文7000字附錄附錄B外文文獻(xiàn)及中文外文文獻(xiàn)及中文翻譯翻譯外文原文外文原文

簡介：天津科技大學(xué)本科生天津科技大學(xué)本科生畢業(yè)設(shè)計外文資料翻譯畢業(yè)設(shè)計外文資料翻譯學(xué)院機(jī)械工程學(xué)院專業(yè)模具設(shè)計制造及自動化姓名牛春明學(xué)號08013111天津科技大學(xué)外文資料翻譯3該階段取得的核心4，根據(jù)這一方法研究了這項工作,有如下A,利用CAD系統(tǒng)設(shè)計的理想目標(biāo)B模型制造的快速成型設(shè)備頻分多路系統(tǒng)所用材料是一個ABS塑料C事先涂有導(dǎo)電涂料的一個電鑄鎳殼必須有導(dǎo)電D無外殼模型E核心的生產(chǎn)是背面環(huán)氧樹脂的抗高溫外殼與具有制冷的銅管管道注塑成型是世界上最常見的方法生產(chǎn)復(fù)雜。商業(yè)塑料部件具有優(yōu)良的尺寸公差。據(jù)對C模具設(shè)計指導(dǎo)，對所處理的塑料重量的32％通過注塑機(jī)，是塑料注塑成型稱為最重要的制造業(yè)之一?？梢钥闯觯罱K成型零件的質(zhì)量，主要是取決于材料的類型，模具設(shè)計和成型過程中設(shè)置。一旦指定要使用的材料和模具，零件質(zhì)量主要取決于成型工藝。成型過程是相當(dāng)復(fù)雜涉及許多工藝參數(shù)如壓力，溫度和時間設(shè)置的變量。這些工藝參數(shù)進(jìn)行優(yōu)化設(shè)置，用來提高零件質(zhì)量，最大限度地挖掘注塑機(jī)的生產(chǎn)能力。受過教育和有經(jīng)驗的個人需要建立和優(yōu)化這樣一個復(fù)雜的過程。這些人控制成型工藝試驗和錯誤的基礎(chǔ)，通常耗時。這種方法在控制成型過程中，嚴(yán)重依賴于運(yùn)營商的直覺和幾個“拇指規(guī)則”運(yùn)營商的發(fā)展而用不同的材料工作過一段時間，壓力，溫度和時間設(shè)置是不同的。塑料行業(yè)是世界上發(fā)展最快的行業(yè)之一，屬于少數(shù)億萬美圓的行業(yè)。在日常生活中幾乎所有的用品都離不開塑料并且大部分都可以用用塑料注射模具的方法生產(chǎn)1。注塑注射成型工藝也以利用低成本制作出各種各樣的形狀及復(fù)雜的幾何圖案著稱2。注塑注射成型工藝是一個循環(huán)過程。可分為填料、注射、冷卻、脫模四個重要階段。塑料注射成型過程開始于往料斗到注塑機(jī)的加熱或注射系統(tǒng)中填入樹脂和適量的添加劑3。灌漿階段就是在注射溫度下用融解的熱塑料注入模

簡介：DOI101007/S0017000423288ORIGINALARTICLEINTJADVMANUFTECHNOL20062861–66FANGJUNGSHIOUCHAOCHANGACHENWENTULIAUTOMATEDSURFACEFINISHINGOFPLASTICINJECTIONMOLDSTEELWITHSPHERICALGRINDINGANDBALLBURNISHINGPROCESSESRECEIVED30MARCH2004/ACCEPTED5JULY2004/PUBLISHEDONLINE30MARCH2005?SPRINGERVERLAGLONDONLIMITED2005ABSTRACTTHISSTUDYINVESTIGATESTHEPOSSIBILITIESOFAUTOMATEDSPHERICALGRINDINGANDBALLBURNISHINGSURFACEFINISHINGPROCESSESINAFREEFORMSURFACEPLASTICINJECTIONMOLDSTEELPDS5ONACNCMACHININGCENTERTHEDESIGNANDMANUFACTUREOFAGRINDINGTOOLHOLDERHASBEENACCOMPLISHEDINTHISSTUDYTHEOPTIMALSURFACEGRINDINGPARAMETERSWEREDETERMINEDUSINGTAGUCHI’SORTHOGONALARRAYMETHODFORPLASTICINJECTIONMOLDINGSTEELPDS5ONAMACHININGCENTERTHEOPTIMALSURFACEGRINDINGPARAMETERSFORTHEPLASTICINJECTIONMOLDSTEELPDS5WERETHECOMBINATIONOFANABRASIVEMATERIALOFPAAL2O3,AGRINDINGSPEEDOF18000RPM,AGRINDINGDEPTHOF20ΜM,ANDAFEEDOF50MM/MINTHESURFACEROUGHNESSRAOFTHESPECIMENCANBEIMPROVEDFROMABOUT160ΜMTO035ΜMBYUSINGTHEOPTIMALPARAMETERSFORSURFACEGRINDINGSURFACEROUGHNESSRACANBEFURTHERIMPROVEDFROMABOUT0343ΜMTO006ΜMBYUSINGTHEBALLBURNISHINGPROCESSWITHTHEOPTIMALBURNISHINGPARAMETERSAPPLYINGTHEOPTIMALSURFACEGRINDINGANDBURNISHINGPARAMETERSSEQUENTIALLYTOAFINEMILLEDFREEFORMSURFACEMOLDINSERT,THESURFACEROUGHNESSRAOFFREEFORMSURFACEREGIONONTHETESTEDPARTCANBEIMPROVEDFROMABOUT215ΜMTO007ΜMKEYWORDSAUTOMATEDSURFACEFINISHINGBALLBURNISHINGPROCESSGRINDINGPROCESSSURFACEROUGHNESSTAGUCHI’SMETHOD1INTRODUCTIONPLASTICSAREIMPORTANTENGINEERINGMATERIALSDUETOTHEIRSPECIFICCHARACTERISTICS,SUCHASCORROSIONRESISTANCE,RESISTANCETOCHEMICALS,LOWDENSITY,ANDEASEOFMANUFACTURE,ANDHAVEINCREASINGLYFJSHIOUUCCACHENWTLIDEPARTMENTOFMECHANICALENGINEERING,NATIONALTAIWANUNIVERSITYOFSCIENCEANDTECHNOLOGY,NO43,SECTION4,KEELUNGROAD,106TAIPEI,TAIWANROCEMAILSHIOUMAILNTUSTEDUTWTEL886227376543FAX886227376460REPLACEDMETALLICCOMPONENTSININDUSTRIALAPPLICATIONSINJECTIONMOLDINGISONEOFTHEIMPORTANTFORMINGPROCESSESFORPLASTICPRODUCTSTHESURFACEFINISHQUALITYOFTHEPLASTICINJECTIONMOLDISANESSENTIALREQUIREMENTDUETOITSDIRECTEFFECTSONTHEAPPEARANCEOFTHEPLASTICPRODUCTFINISHINGPROCESSESSUCHASGRINDING,POLISHINGANDLAPPINGARECOMMONLYUSEDTOIMPROVETHESURFACEFINISHTHEMOUNTEDGRINDINGTOOLSWHEELSHAVEBEENWIDELYUSEDINCONVENTIONALMOLDANDDIEFINISHINGINDUSTRIESTHEGEOMETRICMODELOFMOUNTEDGRINDINGTOOLSFORAUTOMATEDSURFACEFINISHINGPROCESSESWASINTRODUCEDIN1AFINISHINGPROCESSMODELOFSPHERICALGRINDINGTOOLSFORAUTOMATEDSURFACEFINISHINGSYSTEMSWASDEVELOPEDIN2GRINDINGSPEED,DEPTHOFCUT,FEEDRATE,ANDWHEELPROPERTIESSUCHASABRASIVEMATERIALANDABRASIVEGRAINSIZE,ARETHEDOMINANTPARAMETERSFORTHESPHERICALGRINDINGPROCESS,ASSHOWNINFIG1THEOPTIMALSPHERICALGRINDINGPARAMETERSFORTHEINJECTIONMOLDSTEELHAVENOTYETBEENINVESTIGATEDBASEDINTHELITERATUREINRECENTYEARS,SOMERESEARCHHASBEENCARRIEDOUTINDETERMININGTHEOPTIMALPARAMETERSOFTHEBALLBURNISHINGPROCESSFIG2FORINSTANCE,ITHASBEENFOUNDTHATPLASTICDEFORMATIONONTHEWORKPIECESURFACECANBEREDUCEDBYUSINGATUNGSTENCARBIDEBALLORAROLLER,THUSIMPROVINGTHESURFACEROUGHNESS,SURFACEHARDNESS,ANDFATIGUERESISTANCE3–6THEBURNISHINGPROCESSISACCOMPLISHEDBYMACHININGCENTERS3,4ANDLATHES5,6THEMAINBURNISHINGPARAMETERSHAVINGSIGNIFICANTEFFECTSONTHESURFACEROUGHNESSAREBALLORROLLERMATERIAL,BURNISHINGFORCE,FEEDRATE,BURNISHINGSPEED,LUBRICATION,ANDNUMBEROFBURNISHINGPASSES,AMONGOTHERS3THEOPTIMALSURFACEBURNISHINGPARAMETERSFORTHEPLASTICINJECTIONMOLDSTEELPDS5WEREACOMBINATIONOFGREASELUBRICANT,THETUNGSTENCARBIDEBALL,ABURNISHINGSPEEDOF200MM/MIN,ABURNISHINGFORCEOF300N,ANDAFEEDOF40ΜM7THEDEPTHOFPENETRATIONOFTHEBURNISHEDSURFACEUSINGTHEOPTIMALBALLBURNISHINGPARAMETERSWASABOUT25MICRONSTHEIMPROVEMENTOFTHESURFACEROUGHNESSTHROUGHBURNISHINGPROCESSGENERALLYRANGEDBETWEEN40AND903–7THEAIMOFTHISSTUDYWASTODEVELOPSPHERICALGRINDINGANDBALLBURNISHINGSURFACEFINISHPROCESSESOFAFREEFORMSURFACE63FIG4SCHEMATICILLUSTRATIONOFTHESPHERICALGRINDINGTOOLANDITSADJUSTMENTDEVICE3PLANNINGOFTHEMATRIXEXPERIMENT31CONFIGURATIONOFTAGUCHI’SORTHOGONALARRAYTHEEFFECTSOFSEVERALPARAMETERSCANBEDETERMINEDEFFICIENTLYBYCONDUCTINGMATRIXEXPERIMENTSUSINGTAGUCHI’SORTHOGONALARRAY8TOMATCHTHEAFOREMENTIONEDSPHERICALGRINDINGPARAMETERS,THEABRASIVEMATERIALOFTHEGRINDERBALLWITHTHEDIAMETEROF10MM,THEFEEDRATE,THEDEPTHOFGRINDING,ANDTHEREVOLUTIONOFTHEELECTRICGRINDERWERESELECTEDASTHEFOUREXPERIMENTALFACTORSPARAMETERSANDDESIGNATEDASFACTORATODSEETABLE1INTHISRESEARCHTHREELEVELSSETTINGSFOREACHFACTORWERECONFIGUREDTOCOVERTHERANGEOFINTEREST,ANDWEREIDENTIFIG5APHOTOOFTHESPHERICALGRINDINGTOOLBPHOTOOFTHEBALLBURNISHINGTOOLTABLE1THEEXPERIMENTALFACTORSANDTHEIRLEVELSFACTORLEVEL123AABRASIVEMATERIALSICAL2O3,WAAL2O3,PABFEEDMM/MIN50100200CDEPTHOFGRINDINGΜM205080DREVOLUTIONRPM120001800024000FIEDBYTHEDIGITS1,2,AND3THREETYPESOFABRASIVEMATERIALS,NAMELYSILICONCARBIDESIC,WHITEALUMINUMOXIDEAL2O3,WA,ANDPINKALUMINUMOXIDEAL2O3,PA,WERESELECTEDANDSTUDIEDTHREENUMERICALVALUESOFEACHFACTORWEREDETERMINEDBASEDONTHEPRESTUDYRESULTSTHEL18ORTHOGONALARRAYWASSELECTEDTOCONDUCTTHEMATRIXEXPERIMENTFORFOUR3LEVELFACTORSOFTHESPHERICALGRINDINGPROCESS32DEFINITIONOFTHEDATAANALYSISENGINEERINGDESIGNPROBLEMSCANBEDIVIDEDINTOSMALLERTHEBETTERTYPES,NOMINALTHEBESTTYPES,LARGERTHEBETTERTYPES,SIGNEDTARGETTYPES,AMONGOTHERS8THESIGNALTONOISES/NRATIOISUSEDASTHEOBJECTIVEFUNCTIONFOROPTIMIZINGAPRODUCTORPROCESSDESIGNTHESURFACEROUGHNESSVALUEOFTHEGROUNDSURFACEVIAANADEQUATECOMBINATIONOFGRINDINGPARAMETERSSHOULDBESMALLERTHANTHATOFTHEORIGINALSURFACECONSEQUENTLY,THESPHERICALGRINDINGPROCESSISANEXAMPLEOFASMALLERTHEBETTERTYPEPROBLEMTHES/NRATIO,Η,ISDEFINEDBYTHEFOLLOWINGEQUATION8Η?10LOG10MEANSQUAREQUALITYCHARACTERISTIC?10LOG10?1NN?I1Y2I?1WHEREYIOBSERVATIONSOFTHEQUALITYCHARACTERISTICUNDERDIFFERENTNOISECONDITIONSNNUMBEROFEXPERIMENTAFTERTHES/NRATIOFROMTHEEXPERIMENTALDATAOFEACHL18ORTHOGONALARRAYISCALCULATED,THEMAINEFFECTOFEACHFACTORWASDETERMINEDBYUSINGANANALYSISOFVARIANCEANOVATECHNIQUEANDANFRATIOTEST8THEOPTIMIZATIONSTRATEGYOFTHE

簡介：EVALUATIONOFHEATMANAGEMENTININJECTIONMOULDTOOLSBAMCCALLA1,PSALLAN1ANDPRHORNSBY2THECONTROLANDMANAGEMENTOFHEATININJECTIONMOULDTOOLSISAVITALREQUIREMENTFOROBTAININGOPTIMUMPRODUCTIONPROCESSINGCONDITIONSTHISPAPERDESCRIBESANINVESTIGATIONTHATCOMPAREDCONVENTIONALMOULDCOOLINGMETHODSWITHARELATIVELYNEWTECHNIQUECALLED‘PULSECOOLINGTECHNOLOGY’PCTTHEPRINCIPLEOFPCTISTHEUSEOFANINTERMITTENTFLOWOFTHECOOLINGMEDIUMINTHEMOULDTOOLWITHACCURATECONTROLOFTHEMOULDCAVITYSURFACETEMPERATUREDURINGTHEINJECTIONMOULDINGCYCLEAMOULDTOOLINSTRUMENTEDFORCAVITYPRESSURE,CAVITYSURFACETEMPERATUREANDMOULDBACKGROUNDTEMPERATUREMEASUREMENTSWASCONSTRUCTEDFORTHESTUDYRESULTSSHOWINGTHEEFFECTIVENESSOFPCTCOMPAREDWITHCONVENTIONALCOOLINGAREPRESENTEDFORPOLYPROPYLENEPP,POLYCARBONATEANDFILLEDPPWITHTALCANDALUMINIUMPOWDERSAREDUCTIONOFUPTO22OFTHECONVENTIONALLYCOOLEDMOULDINGCYCLETIMEFORUNFILLEDPPHASBEENRECORDEDWHENPULSEDMOULDCOOLINGWASUSEDKEYWORDSINJECTIONMOULDING,MOULDCOOLING,PULSEDCOOLING,MOULDTEMPERATURECONTROLINTRODUCTIONTHEOBJECTIVEOFTHETEMPERATURECONTROLSYSTEMINANINJECTIONMOULDTOOLISTOMAINTAINACONSISTENTCAVITYSURFACETEMPERATURECYCLETHATISESSENTIALFORPARTREPRODUCIBILITYININJECTIONMOULDINGCHANGESINTHECAVITYSURFACETEMPERATURECYCLECANRESULTINAVARIATIONINPROPERTIES,SUCHASSHRINKAGE,INTERNALSTRESS,WARPAGEANDTHESURFACEQUALITYOFMOULDINGSTHEEFFICIENCYOFTHECOOLINGSYSTEMISAMAJORFACTORTHATWILLAFFECTTHEOVERALLCYCLETIME,ASITISTHETIMETOCOOLTHEMOULDINGFROMITSINJECTIONTEMPERATURETOATEMPERATUREATWHICHITCANBEEJECTEDFROMTHEMOULDTOOLTHATTYPICALLYFORMSTHELARGESTPORTIONOFTHEMOULDINGCYCLETIMETHETHERMALPROPERTIESOFTHEMOULDMATERIAL,THEDESIGNOFTHECOOLINGCHANNELS,THEPARTSECTIONTHICKNESS,THEPROPERTIESOFTHEPROCESSEDMATERIALANDTHETEMPERATUREOFTHECOOLINGMEDIUMWILLALLCONTRIBUTETOTHEEFFICIENCYOFTHETOOL1NUMEROUSCOMMERCIALPRODUCTSHAVEBEENDESIGNEDTOIMPROVETHEEFFICIENCYOFTHEREMOVALOFTHEHEATFROMATHERMOPLASTICSINJECTIONMOULDTOOLEXAMPLESOFSOMEOFTHESEAREASFOLLOWSIALLOYSWITHHIGHTHERMALCONDUCTIVITIESBASEDONBERYLLIUMANDCOPPERHAVEBEENUSEDFORTHEPRODUCTIONOFMOULDINSERTSIICONFORMALCOOLINGCHANNELSHAVEBEENUSEDTOACHIEVEUNIFORMHEATREMOVALFROMCOMPLEXMOULDEDSECTIONSIIICOOLINGPROBESANDSPECIALDESIGNSTOCREATETURBULENTFLOWINTHECOOLINGAGENTALLOFTHESEFEATURESCANOFFERSIGNIFICANTBENEFITSTOTHEEFFICIENCYOFTHECOOLINGOFTHEMOULDTOOL,BUTTHEYDONOTPROVIDEFORTHEMANAGEMENTOFTHEHEATEXTRACTIONINTHEMOULDTOOLTHECONVENTIONALMETHODOFCOOLINGTHATISUSEDINTHEINDUSTRYINVOLVESATEMPERATURECONTROLUNITTHATSUPPLIESACOOLINGFLUIDTOTHEMOULDTOOLATASETTEMPERATURETHESENSORUSEDTOCONTROLTHETEMPERATUREOFTHECOOLANTCANBESITUATEDINTHEMOULDTOOLORINTHECONTROLUNITTHEMAINFEATUREOFTHISMETHODOFCOOLINGISTHATTHECOOLANTISCONSTANTLYFLOWINGANDTHATTYPICALLYONLYONECONTROLLINGSENSORISUSEDONAMOULDTOOLOVERTHELAST15YEARS,AMOULDCOOLINGPROCESSTHATCLAIMSTOEFFECTIVELYMANAGETHEHEATTRANSFERININJECTIONMOULDTOOLSHASBEENDEVELOPED2,3THEPROCESSKNOWNAS‘PULSEDCOOLINGTECHNOLOGY’OR‘PCT’OPERATESWITHCONTROLLEDPULSESOFTHECOOLANTTOSEPARATECOOLINGZONESINTHEMOULDTOOLITALSOUSESTHEHEATSUPPLIEDBYTHEINJECTEDRESINMELTTOMAINTAINTHETEMPERATUREOFTHETOOLSOTHATONLYTHEEXCESSHEATFROMTHATSOURCEISEXTRACTEDFROMTHEMOULD2,3ABRIEFDESCRIPTIONOFTHEOPERATIONOFPCTISASFOLLOWSITHEMOULDISINITIALLYHEATEDBYTHEPOLYMERTHATISMOULDEDDURINGTHESETUPPROCEDUREFORTHETOOLALTERNATIVELYTHETOOLCANBEINITIALLYPRIMEDBYUSINGANAUXILIARYHEATINGSYSTEMIIWHENTHEMOULDREACHESTHESETTEMPERATURETHEPULSEDCOOLINGCONTROLTAKESOVERTHEMOULDSURFACETEMPERATUREINEACHOFTHEZONESOFTHETOOLISUSEDTOCONTROLTHEDEMANDFORCOOLANTIIITHEPCTCONTROLISPROGRAMMEDTOSUPPLYPULSESOFTHECOOLINGFLUIDONLYWHENTHEMOULDSURFACESENSORSDEMANDIT1WOLFSONCENTREFORMATERIALSPROCESSING,BRUNELUNIVERSITYUXBRIDGEUB83PH,UK2SCHOOLOFMECHANICALANDAEROSPACEENGINEERING,QUEENSUNIVERSITYBELFAST,BELFASTBT95AH,UKCORRESPONDINGAUTHOR,EMAILPETERALLANBRUNELACUK26?2007INSTITUTEOFMATERIALS,MINERALSANDMININGPUBLISHEDBYMANEYONBEHALFOFTHEINSTITUTERECEIVED27FEBRUARY2006ACCEPTED25OCTOBER2006DOI101179/174328907X174593PLASTICS,RUBBERANDCOMPOSITES2007VOL36NO1THETALCFILLEDPPCOMPOUNDSWEREMADEBYBLENDINGPPPOWDERGROUNDFROMPELLETS,WITHTHEDRIEDTALCPOWDERINAVBLENDERANDTHENCOMPOUNDINGTHEMIXINACOROTATINGTWINSCREWEXTRUDERABETOLTS40THEMOULDINGTRIALSFORBOTHCONVENTIONALCOOLINGANDPULSEDCOOLINGWERECARRIEDOUTWITHINJECTIONGATES1AND3ONTHEENDSOFTHETENSILEBARCAVITIESFIG2WHENTHEBASICMOULDINGCONDITIONSHADBEENESTABLISHEDFORAMOULDINGRUN,THECYCLEWASFINALLYOPTIMISEDBYTHEUSEOFCAVITYPRESSUREMONITORINGTOSETTHESTROKEPOSITIONATWHICHINJECTIONPRESSUREWASSWITCHEDTOHOLDINGPRESSURETHEINJECTION–MOULDINGMACHINEWASSETTOOPERATEINTHEFULLYAUTOMATICMODEANDWASALLOWEDTOSTABILISEBEFOREANYREADINGSWERERECORDEDONTHEDATAACQUISITIONSYSTEMAFTERTHEMOULDINGCONDITIONSHADBEENSETFORAPARTICULARRESINCOMPOUND,THESAMECONDITIONSWEREUSEDFORBOTHCONVENTIONALCOOLINGANDPCTTHISMEANTTHATANYDIFFERENCEINTHECYCLETIMEBETWEENTHETWOSETSOFMOULDINGSCOULDBEDIRECTLYRELATEDTOTHEMOULDCOOLINGMETHODUSEDTYPICALMOULDCAVITYPRESSUREANDTEMPERATURETRACESARESHOWNINFIG4AANDBRESPECTIVELYTHEMOULDCOOLINGTIMEISTAKENFROMTHEPOINTWHENTHECAVITYISVOLUMETRICALLYFULL,ATTHECHANGEOVERFROMINJECTIONPRESSURETOHOLDINGPRESSURETOTHEPOINTWHENTHECAVITYPRESSUREDROPPEDTOATMOSPHERICTHECYCLETIMEWASESTABLISHEDFROMTHETEMPERATURESENSORPROFILES,ASINDICATEDINFIG4BTHEMOULDINGSWEREPRODUCEDUSINGBOTHDIRECTCOOLINGANDPULSEDCOOLINGATVARIOUSSETMOULDTEMPERATURESFORTHEPULSEDCOOLINGEXPERIMENTS,THECOOLANTTEMPERATUREWASSETAT11UCTHEMOULDFORTHETRIALSWASSETUPACCORDINGTOTHEPRINCIPLESOFPULSEDCOOLING32COMPONENTDRAWINGSHOWINGRUNNER,GATESANDLOCATIONSOFFOURCAVITYPRESSURE–TEMPERATURETRANSDUCERSMCCALLAETALEVALUATIONOFHEATMANAGEMENTININJECTIONMOULDTOOLS28PLASTICS,RUBBERANDCOMPOSITES2007VOL36NO1

簡介：1文獻(xiàn)綜述1引言沖壓模具是沖壓生產(chǎn)必不可少的工藝裝備，是技術(shù)密集型產(chǎn)品。沖壓件的質(zhì)量、生產(chǎn)效率以及生產(chǎn)成本等，與模具設(shè)計和制造有直接關(guān)系。模具設(shè)計與制造技術(shù)水平的高低，是衡量一個國家產(chǎn)品制造水平高低的重要標(biāo)志之一，在很大程度上決定著產(chǎn)品的質(zhì)量、效益和新產(chǎn)品的開發(fā)能力。2005年2008年，我國沖壓模具產(chǎn)品均出口較大幅度的增長。2009年在全球高壓鍋爐管市場總需求量下降的情況下，國際采購商通過國內(nèi)某網(wǎng)站采購沖壓模具的數(shù)量仍逆勢上揚(yáng)。我國沖壓模具的國際競爭力正在不斷提升。根據(jù)我國海關(guān)統(tǒng)計資料顯示，2005年2008年，我國沖壓模具產(chǎn)品均出口較大幅度的增長。2008年，即使遭受全球金融危機(jī)，我們沖壓模具出口金額達(dá)411億美元，比2007年的326億美元增長了26。另外，2009年在全球高壓鍋爐管市場總需求量下降的情況下，國際采購商通過國內(nèi)某網(wǎng)站采購沖壓模具的數(shù)量仍逆勢上揚(yáng)。從全年采購情況來看，總體趨于上漲的趨勢。其中，2009年下半年回暖明顯，國際采購商借此網(wǎng)站采購頻次約616頻次，比上半年的288頻次增長了114％。雖然近年來我國模具行業(yè)發(fā)展迅速，但是離國內(nèi)的需要和國際水平還有很大的差距。差距較大主要表現(xiàn)在（1）標(biāo)準(zhǔn)化程度低。（2）模具制造精度低、周期長。解決這些問題主要體現(xiàn)在模具設(shè)計上，故改善模具設(shè)計的水平成為拉近差距的關(guān)鍵性問題。若要很好的設(shè)計出一副沖壓模具，就必須去了解沖壓模具的歷史、現(xiàn)狀以及發(fā)展趨勢。2主體21沖壓模具的發(fā)展歷史我國考古發(fā)現(xiàn)，早在2000多年前，我國已有沖壓模具被用于制造銅器，證明了中國古代沖壓成型和沖壓模具方面的成就就在世界領(lǐng)先。1953年，長春第一汽車制造廠在中國首次建立了沖模車間，該廠于1958年開始制造汽車覆蓋件模具。我國于20世紀(jì)60年代開始生產(chǎn)精沖模具。在走過了溫長的發(fā)展道路之后，目前我國已形成了300多億元（未包括港、澳、臺的統(tǒng)計數(shù)字，下同）各類沖壓模具的生產(chǎn)能力。浙江寧波3色列公司的DIMATRON，還引進(jìn)了BUTODBD、DBTIB等軟件及法國MARTADARAVISION公司用于汽車及覆蓋件模具的EUCLIDIS等專用軟件。國內(nèi)汽車覆蓋件模具生產(chǎn)企業(yè)普遍采用了DBD/DBM技術(shù)。DL圖的設(shè)計和模具結(jié)構(gòu)圖的設(shè)計均已實現(xiàn)二維DBD，多數(shù)企業(yè)已經(jīng)向三維過渡，總圖生產(chǎn)逐步代替零件圖生產(chǎn)。且模具的參數(shù)化設(shè)計也開始走向少數(shù)模具廠家技術(shù)開發(fā)的領(lǐng)域。在沖壓成型DBE軟件方面，除了引進(jìn)的軟件外，華中科技大學(xué)、吉林大學(xué)、湖南大學(xué)等都已研發(fā)了較高水平的具有自主知識產(chǎn)權(quán)的軟件，并已在生產(chǎn)實踐中得到成功應(yīng)用，產(chǎn)生了良好的效益?？焖僭停≧P）與傳統(tǒng)的快速經(jīng)濟(jì)模具相結(jié)合，快速制造大型汽車覆蓋件模具，解決了原來低熔點合金模具靠樣件澆鑄模具，模具精度低、制件精度低，樣件制作難等問題，實現(xiàn)了以三維DBD模型作為制模依據(jù)的快速模具制造，并且保證了制件的精度，為汽車行業(yè)新車型的開發(fā)、車身快速試制提供了覆蓋件制作的保證，它標(biāo)志著RPM應(yīng)用于汽車車身大型覆蓋件試制模具已取得了成功。圍繞著汽車車身試制、大型覆蓋件模具的快速制造，今年來也涌現(xiàn)出一些新的快速成型方法，例如目前已開始在生產(chǎn)中應(yīng)用俄無模多點成型及激光沖擊和電磁成型等技術(shù)。它們都表現(xiàn)出了降低成本、提高效率等優(yōu)點。（2）模具設(shè)計與制造能力狀況在國家產(chǎn)業(yè)政策的正確引導(dǎo)下，經(jīng)過幾十年努力，現(xiàn)在我國沖壓模具的設(shè)計與制造能力已達(dá)到較高水平，包括信息工程和虛擬技術(shù)等許多現(xiàn)代設(shè)計制造技術(shù)已在很多模具企業(yè)得到應(yīng)用。雖然如此，我國的沖壓模具設(shè)計制造能力與市場需要和國際先進(jìn)水平相比仍有較大差距。這些主要表現(xiàn)在高檔轎車和大中型汽車覆蓋件模具及高精度沖模方面，無論在設(shè)計還是加工工藝和能力反面，都有較大差距。轎車覆蓋件模具，具有設(shè)計和制造難度大，質(zhì)量和精度要求高的特點，可代表覆蓋件模具的水平。雖然在設(shè)計制造方面和手段方面已基本達(dá)到了國際水平，模具結(jié)構(gòu)功能方面也接近國際水平，在轎車模具國產(chǎn)化進(jìn)程中前進(jìn)了一大步，但在制造質(zhì)量、進(jìn)度、制造周期等方面，與國外相比還存在一定的差距。標(biāo)志沖模技術(shù)先進(jìn)水平的多工位級進(jìn)模和多功能模具，是我國重點發(fā)展的精密模具品種。有代表性的是集機(jī)電一體化的鐵芯精密自動閥片多功能模具，已基本達(dá)到國際水平。但總體上和國外多工位級進(jìn)模相比，在制造精度、使用壽命、模具結(jié)構(gòu)和功能上，仍存在一定差距。汽車覆蓋件模具制造技術(shù)正在不斷地提高和完善，高精度、高效益加工設(shè)備的使用越來越廣泛。高性能的五軸高速銑床和三軸的高速銑床的應(yīng)用已越來越多。ND、DND技術(shù)的應(yīng)用越來越成熟，可以進(jìn)行傾角加工和超精加工。這些都提高了模具型面加工精度，提高了模具的質(zhì)量，縮短了模具的制造周期。模具表面強(qiáng)化技術(shù)得到廣泛應(yīng)用。工藝成熟、無污染、成本

簡介：CHINESEJOURNALOFAERONAUTICSCHINESEJOURNALOFAERONAUTICS212008247251WWWELSEVIERCOM/LOCATE/CJAHEADPURSUITVARIABLESTRUCTUREGUIDANCELAWFORTHREEDIMENSIONALSPACEINTERCEPTIONGELIANZHENG,SHENYI,GAOYUNFENG,ZHAOLIJUNDEPARTMENTOFCONTROLSCIENCEANDENGINEERING,HARBININSTITUTEOFTECHNOLOGY,HARBIN150001,CHINARECEIVED21SEPTEMBER2007ACCEPTED25DECEMBER2007ABSTRACTTHISARTICLEAIMSTODEVELOPAHEADPURSUITHPGUIDANCELAWFORTHREEDIMENSIONALHYPERVELOCITYINTERCEPTION,SOTHATTHEEFFECTOFTHEPERTURBATIONINDUCEDBYSEEKERDETECTIONCANBEREDUCEDONTHEBASISOFANOVELHPTHREEDIMENSIONALGUIDANCEMODEL,ANONLINEARVARIABLESTRUCTUREGUIDANCELAWISPRESENTEDBYUSINGLYAPUNOVSTABILITYTHEORYTHEGUIDANCELAWPOSITIONSTHEINTERCEPTORAHEADOFTHETARGETONITSFLIGHTTRAJECTORY,ANDTHESPEEDOFTHEINTERCEPTORISREQUIREDTOBELOWERTHANTHATOFTHETARGETANUMERICALEXAMPLEOFMANEUVERINGBALLISTICTARGETINTERCEPTIONVERIFIESTHERIGHTNESSOFTHEGUIDANCEMODELANDTHEEFFECTIVENESSOFTHEPROPOSEDMETHODKEYWORDSHEADPURSUITTHREEDIMENSIONALGUIDANCEMODELNONLINEARVARIABLESTRUCTURELYAPUNOVSTABILITYTHEORYGUIDANCELAW1INTRODUCTION1INTACTICALBALLISTICMISSILEINTERCEPTION,MANYINTERCEPTORSEMPLOYANINFRAREDSEEKERTODETECTTHETARGETHOWEVER,THEDETECTIONPRECISIONISOFTENDEGRADEDBYAERODYNAMICHEATING1TOSOLVETHEAERODYNAMICABLATIONPROBLEM,AHEADPURSUITHPGUIDANCELAW,WHICHPOSITIONSTHEINTERCEPTORMISSILEAHEADOFTHETARGETONITSFLIGHTTRAJECTORYTODESTROYTHETARGET,HASBEENDEVELOPEDRECENTLY2USINGTHISGUIDANCELAW,THEINTERCEPTORCANFLYINTHESAMEDIRECTIONWITHTHETARGETATALOWERSPEEDTHANTHATOFTHETARGETCOMPAREDTOAHEADONENGAGEMENT,THELOWCLOSINGSPEEDISACHIEVEDWITHREDUCEDENERGYREQUIREMENTSTHEHPGUIDANCEMETHODISFURTHERIMPROVEDINREFS34,WHERETHERELATIVEMOTIONMODELISSEPARATEDINTOTWOPERPENDICULARCHANNELSANDTHEGUIDANCEPROBLEMCANBETREATEDASAPLANARPROBLEMINEACHOFTHOSECORRESPONDINGAUTHORTEL8645186418285EMAILADDRESSGELZHITEDUCNCHANNELSBASEDUPONTHEPLANARMODEL,AHPVARIABLESTRUCTUREGUIDANCELAWISTHENDEVELOPEDHOWEVER,ASTHEACTUALMISSILEINTERCEPTIONOCCURSINTHREEDIMENSIONALSPACE,ATHREEDIMENSIONALHPGUIDANCEMETHODISMOREUSEFULINPRACTICALAPPLICATIONSVARIOUSCLASSICGUIDANCEMETHODSHAVEBEENEXAMINEDFORIMPLEMENTATIONOFTHREEDIMENSIONALGUIDANCEINTERCEPTIONSINCETHEORIGINATIONOFTHETHREEDIMENSIONALPUREPROPORTIONALNAVIGATIONGUIDANCELAWPROPOSEDBYADLER5REFS611HAVEDEVELOPEDTHETHREEDIMENSIONALGUIDANCEMODELANDGIVENAGUIDANCELAWBASEDONLYAPUNOVSTABILITYTHEORYTHESEGUIDANCELAWSAREONLYSUITABLEFORHEADONINTERCEPTION,THEIRINTERCEPTIONSTYLESANDKINEMATICSMODELSAREDIFFERENTFROMTHEHPGUIDANCEMETHODASANINTUITIVEANDROBUSTCONTROLTECHNIQUE,THESLIDINGMODEVARIABLESTRUCTURECONTROL1215HASBEENUTILIZEDINVARIOUSGUIDANCEAPPLICATIONSTOADDRESSHIGHLYNONLINEARSYSTEMSGELIANZHENGETAL/CHINESEJOURNALOFAERONAUTICS212008247251249MT00LIM0,LIM0RRΘΘ→→8MT00LIM0,LIM0RRΦΦ→→9THEOBJECTIVEOFTHEHPGUIDANCELAWISTOBRINGTHEINTERCEPTORTOTHEPOINT,WHICHISCONFINEDBYEQS89HENCE,THEINTERCEPTOR’SLEADANGLESMΘANDMΦA(chǔ)REREQUIREDTOBEPROPORTIONALTOTHETARGET’SLEADANGLESRELATIVETOLOSM1TM2T,NNΦΦΘΘ10WHEREN1ANDN2ARETHEGUIDANCECONSTANTSTHUS,THERELATIONSMENTIONEDEARLIERCANGUARANTEETHATΘMVANISHESWITHΘT,ANDΦMVANISHESWITHΦTITISTHENNECESSARYTOFINDOUTTHERELATIONBETWEENTHEANGULARCONDITIONDEFINEDBYEQ10ANDTHEINTERCEPTORACCELERATION3HPVARIABLESTRUCTUREGUIDANCELAW31VARIABLESTRUCTURECONTROLLAWCONSIDERINGTHENONLINEARMULTIPLEINPUTMULTIPLEOUTPUTMIMOUNCERTAINSYSTEM12,,,TTTTTXFXGXUGXW?11WHEREN∈RXISTHESTATEVARIABLE,PT∈RUTHECONTROLVARIABLE,AND,TFXTHEUNCERTAINNONLINEARITEM1,TGXAND2,TGXAREVECTORFUNCTIONS,WHICHHAVESUITABLEDIMENSIONST∈WSRISTHEACCELERATIONDISTURBANCEOFTHETARGETANDLIMITEDBY0TB?00VV?ITISEASILYCHECKEDTHAT?00VXHENCE,THESYSTEMISASYMPTOTICALLYSTABLE,ANDTHECONDITIONSOFTHESLIDINGMODEVARIABLESTRUCTURECONTROLTHEORYARESATISFIED,THUSLEMMA1HOLDS32THEDESIGNOFNONLINEARGUIDANCELAWITFOLLOWSTHATTOREALIZETHECONTROLLAWONEONLYNEEDSTOKNOWTHESCOPEOFACCELERATIONOFTHETARGET,ANDITCANBEAPPLIEDINTHECOURSEOFINTERCEPTINGTHEUNKNOWNACCELERATIONTARGETUSUALLYNOCONTROLISTAKENINTHELOSDIRECTION,ASLONGASOTHERPARAMETERSAREKEPTSLIDINGONTHESLIDINGSURFACEWHENTHETARGETCATCHESTHEINTERCEPTOR,THEGUIDANCECONTROLISCOMPLETEDTHEOTHERCOUPLINGPARAMETERSCANBETREATEDASDISTURBANCES,SOONECANDESIGNTHEGUIDANCELAWBYUSINGTHEDESIGNMETHOD16OFSINGLECHANNELTHEAUTHORSHAVEDESIGNTHENONLINEARVARIABLECONTROLGUIDANCELAWBYUSINGTHEYAWCHANNELASANEXAMPLETHEAIMISTOBRINGTHESYSTEMINTOTHESLIDINGSURFACEANDKEEPTHEDYNAMICALCHARACTERISTICSOFTHESYSTEMACCORDINGTOEQS11,1314,THEVARIABLESAREDEFINEDASUTMZAISTHECONTROLVARIABLETTZWAISTHEACCELERATIONOFTHETARGET,WHICHISASYSTEMDISTURBANCE,12XXX