Two types of iterative learning control schemes, previous cycle learning (PCL) and current cycle learning (CCL), are used to eliminate repeatable run-out (RRO) disturbance in a hard disk drive (HDD) servomechanism. The convergence conditions of two learning control schemes have been explored in detail. The analysis shows that PCL must possess a relative degree of zero. The CCL scheme, on the other hand allows a relative degree of one for a certain range of frequencies to be tracked. To illustrate and compare the applicability and effectiveness of the two ILC schemes for HDD RRO problems, a number of simulations are conducted under a noise contaminated environment.
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