Inthispaper,iterativelearningcontrol(ILC)designisstudiedforaniteration-varyingtrackingprobleminwhichreferencetrajectoriesaregeneratedbyhigh-orderinternalmodels(HOIM).AnHOIMformulatedasapolynomialoperatorbetweenconsecutiveiterationsdescribesthechangesofdesiredtrajectoriesintheiterationdomainandmakestheiterativelearningproblembecomeiterationvarying.TheclassicalILCfortrackingiteration-invariantreferencetrajectories,ontheotherhand,isaspecialcaseofHOIMwherethepolynomialrenderstoaunitycoefficientoraspecialfirst-orderinternalmodel.ByinsertingtheHOIMintoP-typeILC,thetrackingperformancealongtheiterationaxisisinvestigatedforaclassofcontinuous-timenonlinearsystems.Time-weightednormmethodisutilizedtoguaranteevalidityofproposedalgorithminasenseofdata-drivencontrol.