2015
DOI: 10.1109/tcst.2014.2327578
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Rational Basis Functions in Iterative Learning Control—With Experimental Verification on a Motion System

Abstract: DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal… Show more

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Cited by 109 publications
(102 citation statements)
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“…1(a), see (102) . The theoretical framework is further extended towards input shaping (103) and rational feedforward structures in (104)- (106) , which have as key advantage that these can exactly compensate non-minimum phase dynamics, see (107) for a detailed exposition, and also (95) (108) (109) for further details and applications. Finally, a strongly related approach that further connects to system identification in Sec.…”
Section: Flexible Tasksmentioning
confidence: 99%
“…1(a), see (102) . The theoretical framework is further extended towards input shaping (103) and rational feedforward structures in (104)- (106) , which have as key advantage that these can exactly compensate non-minimum phase dynamics, see (107) for a detailed exposition, and also (95) (108) (109) for further details and applications. Finally, a strongly related approach that further connects to system identification in Sec.…”
Section: Flexible Tasksmentioning
confidence: 99%
“…Norm-optimal ILC is an important class of ILC algorithms, e.g., [1,21,15,2,19], where f jþ1 is determined from the solution of an optimization problem. Norm-optimal ILC with basis functions [4,5,34,33] is an extension of the norm-optimal ILC framework, where the feed forward is generated using a set of basis functions. The optimization criterion for the present paper defined as follows.…”
Section: Extending Norm-optimal Iterative Learning Control With Basismentioning
confidence: 99%
“…In the present paper, Fðh j Þ is chosen linearly in h j , such that e z jþ1 is linear in h j . Consequently, the performance criterion (7) is quadratic in h jþ1 and hence an analytic solution to (8) exists [5,34]. The structure of Fðh j Þ is part of the controller design and presented in Section 5.…”
Section: Extending Norm-optimal Iterative Learning Control With Basismentioning
confidence: 99%
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