简介：这份报纸为非线性的量的一个班涉及一个过滤问题有多信道的nondemolition大小的随机的系统。系统观察动力学被bosonic的量维纳过程驾驶的随机的微分方程处于真空状态回答的MarkovianHudson-Parthasarathy量管理。作为系统变量的函数，联合操作符的Hamiltonian和系统地被假定在一张Weyl量子化表格被表示。用Wigner-Moyal阶段空间框架，我们为在大小上调节的系统的以后的伪特征功能(QCF)获得一个随机的integro微分的方程。这个方程是与大小联系的革新过程驾驶的Belavkin-Kushner-Stratonovich随机的主人方程的一个空间Fourier领域代表。我们在联合的线性系统地的情况中讨论以后的QCF动力学的一张特定的表格并且构画出以后的量状态的Gaussian近似。

简介：Inthispaper,theoptimalcontrolofaclassofgeneralaffinenonlineardiscrete-time(DT)systemsisundertakenbysolvingtheHamiltonJacobi-Bellman(HJB)equationonlineandforwardintime.Theproposedapproach,referrednormallyasadaptiveorapproximatedynamicprogramming(ADP),usesonlineapproximators(OLAs)tosolvetheinfinitehorizonoptimalregulationandtrackingcontrolproblemsforaffinenonlinearDTsystemsinthepresenceofunknowninternaldynamics.Boththeregulationandtrackingcontro...

简介：ThispaperdevelopsanewmethodtodealwiththerobustH-infinitycontrolproblemforaclassofuncertainswitchednonlinearsystemsbyusingintegralslidingmodecontrol.ArobustH-infinityintegralslidingsurfaceisconstructedsuchthattheslidingmodeisrobuststablewithaprescribeddisturbanceattenuationlevelγforaclassofswitchingsignalswithaveragedwelltime.Furthermore,variablestructurecontrollersaredesignedtomaintainthestateofswitchedsystemontheslidingsurfacefromtheinitialtime.Anumericalexampleisgiventoillustratetheeffectivenessoftheproposedmethod.

简介：Anewdesignschemeofstableadaptivefuzzycontrolforaclassofnonlinearsystemsisproposedinthispaper.TheT-Sfuzzymodelisemployedtorepresentthesystems.First,theconceptoftheso-calledparalleldistributedcompensation(PDC)andlinearmatrixinequality(LMI)approachareemployedtodesignthestatefeedbackcontrollerwithoutconsideringtheerrorcausedbyfuzzymodeling.SufficientconditionswithrespecttodecayrateαarederivedinthesenseofLyapunovasymptoticstability.Finally,theerrorcausedbyfuzzymodelingisconsideredandtheinput-to-statestable(ISS)methodisusedtodesigntheadaptivecompensationtermtoreducetheeffectofthemodelingerror.Bythesmall-gaintheorem,theresultingclosed-loopsystemisprovedtobeinput-to-statestable.Theoreticalanalysisverifiesthatthestateconvergestozeroandallsignalsoftheclosed-loopsystemsarebounded.TheeffectivenessoftheproposedcontrollerdesignmethodologyisdemonstratedthroughnumericalsimulationonthechaoticHenonsystem.

简介：Adiscretegain-varyingunknowninputobserver(UIO)methodispresentedforactuatorfaultdetectionandisolation(FDI)problemsinthispaper.Anovelresidualschemetogetherwithamovinghorizonthresholdisproposed.ThisdesignmethodologyisappliedtoanonlinearF16systemwithpolynomialaerodynamicscoefficientexpressions,wherethecoefficientexpressionsfortheF16systemandUIOsmaybeslightlydifferent.ThesimulationresultsillustratethatasatisfactoryFDIperformancecanbeachievedevenwhentheF16systemisundertheenvironmentofmodeluncertainties,exogenousnoiseandmeasurementerrors.

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简介：这份报纸在非线性的系统的相等的linearization处理直角的函数的想法。块脉搏(BP)功能把有效工具给近似复杂问题。这个工作的目的在在linearization的过程把BP功能的性质用作直角的功能上。BP函数被用来在时间域建议一个相等的linearization方法决定未知linearization系数。建议方法的精确性与另外的相等的linearization相比来临，包括规定linearization和双标准linearization方法。这研究在静止随机的刺激下面利用了非线性的凡derPol振荡器系统表明建议方法的可行性。分析方法的有效性被使用非线性的不同价值和刺激的紧张验证。而且，由比较吝啬平方的回答和频率反应，为大量非线性的线性化的系统的功能描绘了现在的方法与另外的方法一致。

简介：Arobustadaptiverepetitivelearningcontrolmethodisproposedforaclassoftime-varyingnonlinearsystems.Nussbaum-gainmethodisincorporatedintothecontroldesigntocounteractthelackofaprioriknowledgeofthecontroldirectionwhichdeterminesthemotiondirectionofthesystemunderanyinput.Itisshownthatthesystemstatecouldconvergetothedesiredtrajectoryasymptoticallyalongtheiterationaxisthroughrepetitivelearning.Simulationiscarriedouttoshowthevalidityoftheproposedcontrolmethod.

简介：活跃力量过滤器(APF)基于电压来源inverter(VSI)是为处理力量质量问题的重要措施之一。算术地，APF模型尽最大努力格子是典型的非线性的。被动的想法是一个强大的工具学习如此的一个非线性的系统的稳定。在这篇论文，四腿的APF的一个州空间的模型被导出，基于哪个为当前的追踪的一个新H无穷控制器从被动观点被建议。它能完成asymptotic不仅在L_2获得的意义追踪，而且骚乱变细。随后，保证theboundedness的一个足够的条件和DC电压的需要的平均数也被给。这个直接条件与电的电路的平衡力量的法律一致。在PSCADplatform上执行的模拟验证新途径的有效性。

简介：这篇论文为非线性的不明确的时间延期的一个类与H无穷性能处理柔韧的可靠指数的稳定和柔韧的随机的稳定的问题有Markovian跳参数的随机的系统。时间延期被假定依赖于系统模式。为这些问题的解决之可能性的延期依赖者条件经由参数依赖者Lyapunovfunctionals被获得。而且，需要的州的反馈控制器能被解决一套线性矩阵不平等设计，这被显示出。最后，模拟被提供表明建议方法的有效性。

简介：Thispaperproposesanewasymptoticattitudetrackingcontrollerforanunderactuated3-degree-of-freedom（DOF）laboratoryhelicoptersystembyusinganonlinearrobustfeedbackandaneuralnetwork（NN）feedforwardterm.Thenonlinearrobustcontrollawisdevelopedthroughamodifiedinner-outerloopapproach.TheapplicationoftheNN-basedfeedforwardistocompensateforthesystemuncertainties.Theproposedcontroldesignstrategyrequiresverylimitedknowledgeofthesystemdynamicmodel,andachievesgoodrobustnesswithrespecttosystemparametricuncertainties.ALyapunov-basedstabilityanalysisshowsthattheproposedalgorithmscanensureasymptotictrackingofthehelicopter＇selevationandtravelmotion,whilekeepingthestabilityoftheclosed-loopsystem.Real-timeexperimentresultsdemonstratethatthecontrollerhasachievedgoodtrackingperformance.

简介：Inthispaper,weaimtosolvethefinitehorizonoptimalcontrolproblemforaclassofdiscrete-timenonlinearsystemswithunfixedinitialstateusingadaptivedynamicprogramming(ADP)approach.Anew-optimalcontrolalgorithmbasedontheiterativeADPapproachisproposedwhichmakestheperformanceindexfunctionconvergeiterativelytothegreatestlowerboundofallperformanceindiceswithinanerroraccordingtowithinfinitetime.Theoptimalnumberofcontrolstepscanalsobeobtainedbythepropo...