Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/19595
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dc.contributor.authorTao, Hongfeng-
dc.contributor.authorZheng, Junhao-
dc.contributor.authorWei, Junyu-
dc.contributor.authorPaszke, Wojciech-
dc.contributor.authorRogers, Eric-
dc.contributor.authorStojanović, Vladimir-
dc.date.accessioned2023-12-13T12:49:12Z-
dc.date.available2023-12-13T12:49:12Z-
dc.date.issued2023-
dc.identifier.issn0959-1524en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/19595-
dc.description.abstractThis paper develops an indirect iterative learning control scheme for batch processes with time-varying uncertainties, input delay, and disturbances. In this paper, a predictor based on a state observer is designed to estimate the future state and to compensate for the input delay. Then a feedback controller based on the estimated state and the set-point error is used to track the specified reference trajectory, where, of the options available, a robust 𝐻∞ controller is designed in the presence of time-varying uncertainties and load disturbances. Then a proportional plus derivative type iterative learning control law is designed. An injection molding process model demonstrates the new method’s effectiveness, and a comparison with a direct-type design is given.en_US
dc.language.isoenen_US
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.sourceJournal of Process Control-
dc.subjectBatch processen_US
dc.subjectIterative learning controlen_US
dc.subjectInput-delayen_US
dc.subjectRepetitive processen_US
dc.subjectRobust H∞ controlen_US
dc.subjectLinear matrix inequalityen_US
dc.titleRepetitive process based indirect-type iterative learning control for batch processes with model uncertainty and input delayen_US
dc.typearticleen_US
dc.description.versionPublisheden_US
dc.identifier.doi10.1016/j.jprocont.2023.103112en_US
dc.type.versionPublishedVersionen_US
Appears in Collections:Faculty of Mechanical and Civil Engineering, Kraljevo

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