Please use this identifier to cite or link to this item:
https://doi.org/10.1109/TSMCC.2004.829304
DC Field | Value | |
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dc.title | Neural-network-based predictive learning control of ram velocity in injection molding | |
dc.contributor.author | Huang, S.N. | |
dc.contributor.author | Tan, K.K. | |
dc.contributor.author | Lee, T.H. | |
dc.date.accessioned | 2014-06-17T02:58:37Z | |
dc.date.available | 2014-06-17T02:58:37Z | |
dc.date.issued | 2004-08 | |
dc.identifier.citation | Huang, S.N., Tan, K.K., Lee, T.H. (2004-08). Neural-network-based predictive learning control of ram velocity in injection molding. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 34 (3) : 363-368. ScholarBank@NUS Repository. https://doi.org/10.1109/TSMCC.2004.829304 | |
dc.identifier.issn | 10946977 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/56788 | |
dc.description.abstract | In this paper, we develop a predictive learning controller for ram velocity of injection molding based on neural networks. We first introduce a model of describing the injection molding, including the time horizon and the batch index. The feedback control plus biased function is proposed for controlling this plant. More specifically, a radial basis function (RBF) network is used to approximate the biased function based on the time horizon. The weights in the RBF are determined by a predictive control scheme based on the batch index. For this algorithm, relevant convergence is investigated. Simulation results reveal that the proposed control can achieve our claims. © 2004 IEEE. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TSMCC.2004.829304 | |
dc.source | Scopus | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.description.doi | 10.1109/TSMCC.2004.829304 | |
dc.description.sourcetitle | IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews | |
dc.description.volume | 34 | |
dc.description.issue | 3 | |
dc.description.page | 363-368 | |
dc.description.coden | ITCRF | |
dc.identifier.isiut | 000222721200012 | |
Appears in Collections: | Staff Publications |
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