畸变电网下PWM整流器鲁棒预测控制研究

畸变电网下PWM整流器鲁棒预测控制研究摘要：畸变电网在现代工业生产中广泛存在，其复杂性和不稳定性对电力系统的稳定运行产生了深远影响。针对畸变电网下PWM整流器的鲁棒控制问题，本文提出了一种基于预测控制的解决方案。首先，通过建立畸变电网下PWM整流器的动态数学模型，利用基于神经网络的系统辨识技术进行参数辨识，建立了一个能够准确反映畸变电网特性的系统模型。然后，采用基于RBF神经网络的预测控制算法进行预测和控制，利用控制器对PWM整流器进行鲁棒性调节，实现了对畸变电网下PWM整流器的鲁棒控制。最后，通过仿真实验验证了该预测控制算法的可行性和有效性。

关键词：畸变电网；PWM整流器；鲁棒控制；预测控制；RBF神经网络

Abstract:Distortedpowergridhasbeenwidelyexistinmodernindustrialproduction,anditscomplexityandinstabilityhaveprofoundimpactonthestableoperationofpowersystem.InordertosolvetherobustcontrolproblemofPWMrectifierunderdistortedpowergrid,thispaperproposesasolutionbasedonpredictivecontrol.Firstly,byestablishingthedynamicmathematicalmodelofPWMrectifierunderdistortedpowergrid,usingthesystemidentificationtechnologybasedonneuralnetworkforparameteridentification,weestablishedasystemmodelthatcanaccuratelyreflectthecharacteristicsofdistortedpowergrid.Then,thepredictivecontrolalgorithmbasedonRBFneuralnetworkisusedforpredictionandcontrol,andthecontrollerisusedtoadjusttherobustnessofPWMrectifier,realizingtherobustcontrolofPWMrectifierunderdistortedpowergrid.Finally,thefeasibilityandeffectivenessofthepredictivecontrolalgorithmareverifiedbysimulationexperiments.

Keywords:Distortedpowergrid;PWMrectifier;Robustcontrol;Predictivecontrol;RBFneuralnetworInrecentyears,theuseofpowerelectronics-basedsystemssuchasPWMrectifiershasincreasedrapidlyduetotheirhighefficiencyandexcellentperformance.However,theoperationofsuchsystemsinadistortedpowergridcancausesignificantchallenges.Thedistortioninthepowergridcanresultinseveralissuessuchasreducedpowerquality,decreasedsystemefficiency,andeveninstability.Therefore,therobustcontrolofPWMrectifiersunderdistortedpowergridconditionshasbecomeanimportantresearchtopic.

Toaddressthischallenge,apredictivecontrolalgorithmbasedonRBFneuralnetworkisproposedinthisstudy.ThealgorithmutilizestheRBFneuralnetworktopredicttheoutputvoltageandcurrentofthePWMrectifierunderdifferentoperatingconditions.ThepredictedvaluesarethenusedbythecontrollertoadjusttherobustnessofthePWMrectifier.ThecontrolobjectiveistomaintainthedesiredoutputvoltageandcurrentofthePWMrectifierunderdistortedpowergridconditions.

Theproposedalgorithmwastestedthroughsimulationexperiments.TheresultsshowedthatthealgorithmwasabletoeffectivelymaintainthedesiredoutputvoltageandcurrentofthePWMrectifierunderdistortedpowergridconditions.ThesimulationsalsoshowedthattheproposedalgorithmhadbetterperformancecomparedtotraditionalPIcontrollers.

Inconclusion,theproposedpredictivecontrolalgorithmbasedonRBFneuralnetworkisaneffectivewaytoachieverobustcontrolofPWMrectifiersunderdistortedpowergridconditions.ThealgorithmcanimprovetheperformanceandstabilityofPWMrectifiers,henceimprovingpowerqualityandefficiency.FurtherresearchcanbeconductedtooptimizethealgorithmforpracticalapplicationsInadditiontotheproposedalgorithmbasedonRBFneuralnetwork,thereareotheradvancedcontrolstrategiesthatcanbeusedforPWMrectifiers.Onesuchstrategyisthemodelpredictivecontrol(MPC)whichisgainingincreasedattentioninrecentyearsduetoitsabilitytohandlecomplexcontrolproblems.MPCisapredictivecontrolmethodthatusesamathematicalmodelofthesystemtopredictthesystem'sfuturebehaviorandoptimizeacostfunctionoverafinitehorizon.TheadvantageofMPCovertraditionalcontroltechniquesisthatitcanhandleconstraintsanduncertainties,makingitasuitablechoiceforpowerelectronicssystems.

AnothercontrolstrategythatcanbeusedforPWMrectifiersisadaptivecontrol.Adaptivecontrolisatypeofcontrolthatadjuststhecontrollerparametersbasedonthechangesinthesystem'sdynamics.Thismeansthatthecontrollercanadapttovaryingoperatingconditions,makingitmoreflexibleandrobust.However,adaptivecontrolrequiresathoroughunderstandingofthesystem,andthedesignofthecontrollercanbemorechallengingcomparedtotraditionalcontrolmethods.

Moreover,theapplicationofartificialintelligence()techniquessuchasfuzzylogic,geneticalgorithms,andreinforcementlearning,hasshownpromisingresultsinthecontrolofpowerelectronicssystems.Forinstance,thefuzzylogiccontroller(FLC)isanon-linearcontroltechniquethatcanhandleuncertaintiesandnon-linearitiesinthesystem.FLCcanbeusedtodevelopacost-effectivecontrolstrategyforPWMrectifiersthatcanachievegoodperformanceunderdistortedpowergridconditions.

Inconclusion,thecontrolofPWMrectifiersisachallengingtaskduetothenon-linearandcomplexnatureofthesystem,andthepresenceofdistortedpowergridconditions.However,advancedcontrolstrategiessuchasMPC,adaptivecontrol,and-basedtechniquesofferapromisingapproachforachievingrobustandefficientcontrolofPWMrectifiers.FutureresearchcanfocusonthedevelopmentandimplementationoftheseadvancedcontrolstrategiesforpracticalapplicationsOneareaofresearchforfuturedevelopmentinPWMrectifiersistheintegrationwithrenewableenergysources,suchaswindandsolarpower.Thefluctuatingnatureofrenewableenergysourcescreateschallengesforstableandefficientoperationofthepowergrid.PWMrectifierscanplayaroleinbalancingthepowersupplyanddemand,andadvancedcontrolstrategiescanbedevelopedtooptimizetheperformanceofthepowergrid.

AnotherareaofresearchistheapplicationofPWMrectifiersinelectricvehicles.Withtheincreasingpopularityofelectricvehicles,thedemandforefficientandreliablepowerconvertersisgrowing.PWMrectifierscanbeusedasbatterychargersandmotordrivesinelectricvehicles.Advancedcontrolstrategiescanbeemployedtoensuresafeandfastcharging,andhigh-performancemotorcontrol.

Moreover,thedevelopmentofhardware-in-the-loop(HIL)simulationplatformscanfacilitatethetestingandvalidationofadvancedcontrolstrategiesforPWMrectifiers.HILsimulationallowsthecontrolalgorithmstobetestedinarealisticenvironment,withouttheneedforexpensiveandtime-consuminghardwaretesting.HILsimulationcanacceleratethedevelopmentanddeploymentofadvancedcontrolstrategiesforPWMrectifiers,andhelptoimprovetheefficiencyandreliabilityofpowerelectronicssystems.

Finally,theintegrationofartificialintelligence()techniques,suchasdeeplearningandreinforcementlearning,canfurtherenhancetheperformanceofPWMrectifiers.techniquescanlearnfromthesystembehaviorandadaptthecontrolstrategiesinreal-time,leadingtoimprovedefficiency,robustness,andreliability.However,thedevelopmentof-basedcontrolalgorithmsrequireslargeamountsoftrainingdataandcomputationalpower,andcarefulconsiderationofsafetyandethicalconcerns.

Insummary,thecontrolofPWMrectifiersisachallengingtask,butadvancedcontrolstrategiesandresearchareassuchasrenewableenergyintegration,electricvehicles,