简介：在没有规模的网络上称为随机的散步免疫策略的新奇免疫策略被建议。与另外的已知的免疫策略不同，这策略如下工作：一个节点随机从网络被选择。从这个节点开始，随机去它的邻居节点之一；如果现在的节点没被使免疫，那么使它免疫并且继续随机的散步；否则回到以前的节点并且随机再走。这个过程被重复直到节点的某个部分被使免疫。由理论分析和数字模拟，我们发现这策略与另外的已知的免疫策略比较是很有效的。

简介：Westudiedtheconjunctionpracticalstabilityandcontrollabilityoflarge-scaleimpulsivecontrolsystemsbyusingthecomparisonsystemsandvectorLyapunovfunctions.Thenthelessconservativesufficientconditionsforconjunctionpracticalstabilityandcontrollabilityoflarge-scaleimpulsivecontrolsystemwereobtained.

简介：Inordertocontrolthelarge-scaleurbantrafficnetworkthroughhierarchicalordecentralizedmethods,itisnecessarytoexploitanetworkpartitionmethod,whichshouldbebotheffectiveinextractingsubnetworksandfasttocompute.Inthispaper,anewapproachtocalculatethecorrelationdegree,whichdeterminesthedesireforinterconnectionbetweentwoadjacentintersections,isfirstproposed.Itisusedasaweightofalinkinanurbantrafficnetwork,whichconsidersboththephysicalcharacteristicsandthedynamictrafficinformationofthelink.Then,afastnetworkdivisionapproachbyoptimizingthemodularity,whichisacriteriontodistinguishthequalityofthepartitionresults,isappliedtoidentifythesubnetworksforlarge-scaleurbantrafficnetworks.Finally,anapplicationtoaspecifiedurbantrafficnetworkisinvestigatedusingtheproposedalgorithm.Theresultsshowthatitisaneffectiveandefficientmethodforpartitioningurbantrafficnetworksautomaticallyinrealworld.

简介：Thispaperstudiestheoptimalcontrolwithzerosteady-stateerrorproblemfornonlinearlarge-scalesystemsaffectedbyexternalpersistentdisturbances.Thenonlinearlarge-scalesystemistransformedintoNnonlinearsubsystemswithinterconnectterms.Basedontheinternalmodelprinciple,adisturbancecompensatorisconstructedsuchthattheithsubsystemwithexternalpersistentdisturbancesistransformedintoanaugmentedsubsystemwithoutdisturbances.Accordingtothesensitivityapproach,theoptimaltrackingcontrollawfortheithnonlinearsubsystemcanbeobtained.Theoptimaltrackingcontrollawforthenonlinearlarge-scalesystemscanbeobtained.Anumericalsimulationshowsthatthemethodiseffective.

简介：Large-scalewindturbinegeneratorsystemshavestrongnonlinearmultivariablecharacteristicswithmanyuncertainfactorsanddisturbances.Automaticcontroliscrucialfortheefficiencyandreliabilityofwindturbines.Onthebasisofsimplifiedandpropermodelofvariablespeedvariablepitchwindturbines,theeffectivewindspeedisestimatedusingextendedKalmanfilter.Intelligentcontrolschemesproposedinthepaperincludetwoloopswhichoperateinsynchronismwitheachother.Atbelow-ratedwindspeed,theinnerloopadoptsadaptivefuzzycontrolbasedonvariableuniverseforgeneratortorqueregulationtorealizemaximumwindenergycapture.Atabove-ratedwindspeed,acontrollerbasedonleastsquaresupportvectormachineisproposedtoadjustpitchangleandkeepratedoutputpower.Thesimulationshowstheeffectivenessoftheintelligentcontrol.

简介：Intheprocedureofthesteady-statehierarchicaloptimizationwithfeedbackforlarge-scaleindustrialprocesses,asequenceofset-pointchangeswithdifferentmagnitudesiscarriedoutontheoptimizationlayer.Toimprovethedynamicperformanceoftransientresponsedrivenbytheset-pointchanges,afilter-basediterativelearningcontrolstrategyisproposed.Intheproposedupdatinglaw,alocal-symmetric-integraloperatorisadoptedforeliminatingthemeasurementnoiseofoutputinformation,asetofdesiredtrajectoriesarespecifiedaccordingtotheset-pointchangessequence,thecurrentcontrolinputisiterativelyachievedbyutilizingsmoothedoutputerrortomodifyitscontrolinputatpreviousiteration,towhichtheamplifiedcoefficientsrelatedtothedifferentmagnitudesofset-pointchangesareintroduced.Theconvergenceofthealgorithmisconductedbyincorporatingfrequency-domaintechniqueintotime-domainanalysis.Numnericalsimulationdemonstratestheeffectivenessoftheproposedstrategy.

简介：由认为城市的下水道网络的流动控制最小化抽水站的电消费，为精力积蓄的分解协作策略在这篇论文基于网络社区分割被开发。描绘城市的下水道网络的稳态流的一个数学模型首先被构造，由有作为限制捕获的结构交通能力的一套代数学的方程组成。因为下水道网络没一般来说有明显的自然层次结构，识别聚类的组是很困难的。通过计算每个边的between海角的一条快网络部门途径成功地被使用与任意的配置识别这些组和一个下水道网络然后能被分解成子网。由集成子网的联合限制，原来的问题根据网络分解被分开成N优化潜水艇问题。每个潜水艇问题局部地被解决，潜水艇问题的答案被协调形成一个适当全球答案。最后，到一个指定大规模下水道网络的一个应用程序也被调查表明建议算法的有效性。