On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise

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dc.contributor.author Saab, Samer S.
dc.date.accessioned 2019-08-20T10:50:25Z
dc.date.available 2019-08-20T10:50:25Z
dc.date.copyright 2005 en_US
dc.date.issued 2019-08-20
dc.identifier.isbn 0780395689 en_US
dc.identifier.uri http://hdl.handle.net/10725/11216
dc.description.abstract Higher-Order Iterative Learning Control (HO-ILC) algorithms use past system control information from more than one past iterative cycle. This class of ILC algorithms have been proposed aiming at improving the learning efficiency and performance. This paper addresses the optimality of HO-ILC in the sense of minimizing the control error covariance matrix in the presence of measurement noise. It is shown that the optimal weighting matrices corresponding to the control information associated with more than one cycle preceding the current cycle are zero. Consequently, an optimal HO-ILC is automatically reduced to an optimal first-order ILC. The system under consideration is a linear discrete-time varying systems with different relative degree between the input and each output. Furthermore, a suboptimal second-order ILC is proposed for a class of nonlinear systems. Based on a numerical example, it is shown that a compatible suboptimal first-order ILC yields better performance than the proposed suboptimal second-order ILC algorithm. en_US
dc.description.sponsorship Institute of Electrical and Electronic Engineers en_US
dc.description.sponsorship IEEE Control Systems Society en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Adaptive control systems -- Congresses en_US
dc.subject Decision making -- Mathematical models -- Congresses en_US
dc.subject System analysis -- Congresses en_US
dc.subject Feedback control systems -- Congresses en_US
dc.title On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise en_US
dc.type Conference Paper / Proceeding en_US
dc.author.school SOE en_US
dc.author.idnumber 199690250 en_US
dc.author.department Computer Science And Mathematics en_US
dc.description.embargo N/A en_US
dc.publication.place Piscataway, N.J. en_US
dc.description.bibliographiccitations Includes bibliographical references. en_US
dc.identifier.doi http://dx.doi.org/10.1109/CDC.2005.1582530 en_US
dc.identifier.ctation Saab, S. S. (2005, December). On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise. In Proceedings of the 44th IEEE Conference on Decision and Control (pp. 2451-2456). IEEE. en_US
dc.author.email ssaab@lau.edu.lb en_US
dc.conference.date December 12-15, 2005 en_US
dc.conference.pages 2451-2456 en_US
dc.conference.place Seville, Spain en_US
dc.conference.subtitle proceedings en_US
dc.conference.title 44th IEEE Conference on Decision and Control, and European Control Conference ECC'05 en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ieeexplore.ieee.org/abstract/document/1582530 en_US
dc.orcid.id https://orcid.org/0000-0003-0124-8457 en_US
dc.publication.date 2005 en_US
dc.author.affiliation Lebanese American University en_US

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