Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/71207
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dc.titleOn initial conditions in iterative learning control
dc.contributor.authorXu, J.-X.
dc.contributor.authorYan, R.
dc.contributor.authorChen, Y.
dc.date.accessioned2014-06-19T03:21:06Z
dc.date.available2014-06-19T03:21:06Z
dc.date.issued2006
dc.identifier.citationXu, J.-X.,Yan, R.,Chen, Y. (2006). On initial conditions in iterative learning control. Proceedings of the American Control Conference 2006 : 220-225. ScholarBank@NUS Repository.
dc.identifier.isbn1424402107
dc.identifier.issn07431619
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/71207
dc.description.abstractInitial conditions, or initial resetting conditions, play a fundamental role in all kinds of iterative learning control methods. In this work we study five different initial conditions, disclose the inherent relationship between each initial condition and corresponding learning convergence (or boundedness) property. The iterative learning control method under consideration is based on Lyapunov theory, which is suitable for plants with time varying parametric uncertainties and local Lipschitz nonlinearities. © 2006 IEEE.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitleProceedings of the American Control Conference
dc.description.volume2006
dc.description.page220-225
dc.description.codenPRACE
dc.identifier.isiutNOT_IN_WOS
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