In　this　paper,　a　PD-type　open-closed-loop　iterative　learning　control　strategy　is　studied　for　linear　time-invariant　system.　By　means　of　Hausdorff-Young　inequality　of　convolution　integral,　the　convergence　of　the　proposed　open-closed-loop　iterative　learning　control　updating　law　is　analyzed　for　a　given　system　in　the　sense　of　Lebesgue-p　norm.　It　is　shown　from　the　theoretical　analysis　that　the　sufficient　condition　for　convergence　in　sense　of　Lebesgue-p　norm　is　dominated　by　not　only　the　derivative　learning　gains　but　also　the　proportional　learning　gains.　A　comparable　conclusion　is　theoretically　discussed　and　the　advantage　of　the　updating　law　is　numerically　simulated.