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dc.contributor.authorIgram, Spencer
dc.contributor.authorAlleyne, Andrew G.
dc.date.accessioned2024-12-24T18:48:44Z
dc.date.available2024-12-24T18:48:44Z
dc.date.copyright1/10/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn0022-0434
dc.identifier.otherds_146_03_031002.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4302789
dc.description.abstractThis work examines a class of distributed linear systems that fit a tree type of hierarchical structure. Therefore, unidirectional information flow from a subsystem higher in the hierarchy impacts subsystems lower in the hierarchy. While prior efforts at control focused on feedback solutions to these systems, this effort introduces Iterative Learning Control as a feedforward controller. This is termed hierarchical iterative learning control (HILC). This HILC can be implemented in parallel with feedback algorithms or can be used in a series feedforward manner assuming stable, or stabilized, subsystems. An augmentation of the standard learning update operators provides stability and monotonic convergence for the proposed approach. A simulation case study highlights the performance of the proposed design approach.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleHierarchical Iterative Learning Control for a Class of Distributed Hierarchical Systems
dc.typeJournal Paper
dc.journal.volume146
dc.journal.issue3
dc.journal.titleJournal of Dynamic Systems, Measurement, and Control
dc.identifier.doi10.1115/1.4064174
dc.journal.fristpage31002-1
dc.journal.lastpage31002-9
dc.page9
dc.treeJournal of Dynamic Systems, Measurement, and Control:;2024:;volume( 146 ):;issue: 003
dc.contenttypeFulltext


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