Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/56946
DC Field | Value | |
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dc.title | Optimal Smith-predictor design based on a GPC approach | |
dc.contributor.author | Tan, K.K. | |
dc.contributor.author | Lee, T.H. | |
dc.contributor.author | Leu, F.M. | |
dc.date.accessioned | 2014-06-17T03:00:29Z | |
dc.date.available | 2014-06-17T03:00:29Z | |
dc.date.issued | 2002-03-06 | |
dc.identifier.citation | Tan, K.K.,Lee, T.H.,Leu, F.M. (2002-03-06). Optimal Smith-predictor design based on a GPC approach. Industrial and Engineering Chemistry Research 41 (5) : 1242-1248. ScholarBank@NUS Repository. | |
dc.identifier.issn | 08885885 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/56946 | |
dc.description.abstract | In this paper, an optimal Smith-predictor design based on a generalized predictive control (GPC) approach is developed. The basic idea is to back-calculate the Smith control parameters based on the GPC control law, which has been designed to minimize a cost function. The design has turned out to be very simple to use. With a second-order model, the primary controller is simply a PID control. With a first-order model, it is a PI controller. The relationship between the control parameters obtained via the GPC approach and a pole placement approach is derived so that the latter approach may be used to derive initial GPC weights for further fine-tuning. Simulation and a real-time experiment illustrate the performance of the thus-designed optimal Smith control system. | |
dc.source | Scopus | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.contributor.department | ELECTRICAL ENGINEERING | |
dc.description.sourcetitle | Industrial and Engineering Chemistry Research | |
dc.description.volume | 41 | |
dc.description.issue | 5 | |
dc.description.page | 1242-1248 | |
dc.description.coden | IECRE | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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