Please use this identifier to cite or link to this item: https://doi.org/10.1109/CDC.2009.5399702
Title: On robust modifications for repetitive learning control
Authors: Yan, R.
Xu, J.-X. 
Issue Date: 2009
Source: Yan, R., Xu, J.-X. (2009). On robust modifications for repetitive learning control. Proceedings of the IEEE Conference on Decision and Control : 440-445. ScholarBank@NUS Repository. https://doi.org/10.1109/CDC.2009.5399702
Abstract: In this paper, we develop two algorithms to robustify repetitive learning control (RLC), which deals with periodic tracking tasks for nonlinear dynamical systems with non-parametric uncertainties. The first robustification algorithm is to apply a projection operator to the control input signals directly. The second robustification algorithm is to add a damping term to the learning law. Both algorithms ensure the boundedness of the learning signals. The effectiveness of the proposed robust algorithms are verified through theoretical analysis and validated through a numerical example. ©2009 IEEE.
Source Title: Proceedings of the IEEE Conference on Decision and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/71213
ISBN: 9781424438716
ISSN: 01912216
DOI: 10.1109/CDC.2009.5399702
Appears in Collections:Staff Publications

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