Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0952-1976(02)00032-5
DC FieldValue
dc.titleLearning-enhanced PI control of ram velocity in injection molding machines
dc.contributor.authorTan, K.K.
dc.contributor.authorTang, J.C.
dc.date.accessioned2014-06-17T02:55:05Z
dc.date.available2014-06-17T02:55:05Z
dc.date.issued2002-02
dc.identifier.citationTan, K.K., Tang, J.C. (2002-02). Learning-enhanced PI control of ram velocity in injection molding machines. Engineering Applications of Artificial Intelligence 15 (1) : 65-72. ScholarBank@NUS Repository. https://doi.org/10.1016/S0952-1976(02)00032-5
dc.identifier.issn09521976
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/56483
dc.description.abstractThis paper presents the development of a new learning enhanced PI control method for cyclical control of the ram velocity in injection molding machines. The overall structure of the control consists of a feedback and a feedforward component. The PI feedback control stabilizes the system, and the feedforward component incorporates an iterative learning control (ILC) algorithm to compensate for nonlinear/unknown dynamics and disturbances, thereby enhancing the performance achievable with feedback control alone. A simple and effective tuning method is further developed for the composite control structure which yields both the PI and ILC gains given only a first-order model. A nonlinear physical model derived for the process serves as the basis for the simulation study of the proposed control scheme. A comparison of the performance achieved with an optimally tuned PI control is also provided to highlight the advantages of the proposed control scheme. © 2002 Elsevier Science Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0952-1976(02)00032-5
dc.sourceScopus
dc.subjectInjection molding
dc.subjectIterative learning control
dc.subjectNonlinear systems
dc.subjectPI control
dc.subjectTracking control
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1016/S0952-1976(02)00032-5
dc.description.sourcetitleEngineering Applications of Artificial Intelligence
dc.description.volume15
dc.description.issue1
dc.description.page65-72
dc.description.codenEAAIE
dc.identifier.isiut000177546600007
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