Track-following control for optical disk drives using an iterative learning scheme

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In this paper, we propose an iterative learning scheme to deal with the periodic off-track errors in the track-following control system for optical disk drives. The periodic errors could be taken into account more effectively by employing an iterative learning algorithm since the errors of the previous period are used to improve the performance of current period. We show a sufficient condition for the convergence of the learning algorithm in the presence of bounded modeling uncertainty. In addition, the effects of the initial state error on the tracking performance are analyzed. Finally, the proposed learning algorithm is demonstrated to be feasible through experiments applying it to the track-following control for an optical disk drive.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
1996-05
Language
English
Article Type
Article
Citation

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, v.42, no.2, pp.192 - 198

ISSN
0098-3063
URI
http://hdl.handle.net/10203/75857
Appears in Collection
EE-Journal Papers(저널논문)
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