Please use this identifier to cite or link to this item: https://doi.org/10.1109/TAC.2003.809164
DC FieldValue
dc.titleFixed point theorem-based iterative learning control for LTV systems with input singularity
dc.contributor.authorXu, J.-X.
dc.contributor.authorYan, R.
dc.date.accessioned2014-06-17T02:50:22Z
dc.date.available2014-06-17T02:50:22Z
dc.date.issued2003-03
dc.identifier.citationXu, J.-X., Yan, R. (2003-03). Fixed point theorem-based iterative learning control for LTV systems with input singularity. IEEE Transactions on Automatic Control 48 (3) : 487-492. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2003.809164
dc.identifier.issn00189286
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/56068
dc.description.abstractIn this note, we address a challenging and open problem: how to design a suitable iterative learning control (ILC) system in the presence of input singularity, which is Incurred by the singularities of the system direct feed-through term. Considering two typical types of input singularities, we first revise the ILC operators accordingly by adding a forgetting factor and incorporating a time-varying learning gain, in the sequel guarantee ILC operators to be contractible. Next, using the Banach fixed-point theorem, we demonstrate that the output sequence can either enter and remains ultimately in a designated neighborhood of the target trajectory, or is bounded by a class κ function. Finally, an illustrative example is presented.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TAC.2003.809164
dc.sourceScopus
dc.subjectFixed-point theorem
dc.subjectInput singularity
dc.subjectIterative learning control (ILC)
dc.subjectLinear time-varying (LTV) systems
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TAC.2003.809164
dc.description.sourcetitleIEEE Transactions on Automatic Control
dc.description.volume48
dc.description.issue3
dc.description.page487-492
dc.description.codenIETAA
dc.identifier.isiut000181541600014
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