In this paper, three iterative learning control (ILC) schemes are developed in the multirate signal processing domain. One is pseudo-downsampled ILC, in which the input update rate is different from the sampling rate of feedback system. The second one is a two-mode ILC, in which the input update rates of ILC are different at low and high frequency bands. The third one is a cyclic pseudo-downsampled ILC, which extends the first scheme by shifting downsampling points in different iterations. Theoretical background and design approaches of these multirate schemes are addressed. Experimental results are presented to highlight the traits of each scheme. The advantage is that these schemes have the ability to learn those error component beyond the learnable bandwidth of a conventional ILC and, therefore, can improve the tracking accuracy substantially. Additionally, the multirate ILC schemes have the abilities to produce good learning transient with the presence of initial state error.