Identification and predictive control of a multistage evaporator

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dc.contributor.author Atuonwu, J. C. -
dc.contributor.author Cao, Yi -
dc.contributor.author Rangaiah, G. P. -
dc.contributor.author Tade, M. O. -
dc.date.accessioned 2011-04-19T23:09:40Z
dc.date.available 2011-04-19T23:09:40Z
dc.date.issued 2010-12-31T00:00:00Z -
dc.identifier.citation J.C. Atuonwu, Y. Cao, G.P. Rangaiah, M.O. Tade, Identification and predictive control of a multistage evaporator, Control Engineering Practice, Volume 18, Issue 12, December 2010, Pages 1418-1428
dc.identifier.issn 0967-0661 -
dc.identifier.uri http://dx.doi.org/10.1016/j.conengprac.2010.08.002 -
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/5215
dc.description.abstract A recurrent neural network-based nonlinear model predictive control (NMPC) scheme in parallel with PI control loops is developed for a simulation model of an industrial-scale five-stage evaporator. Input-output data from system identification experiments are used in training the network using the Levenberg- Marquardt algorithm with automatic differentiation. The same optimization algorithm is used in predictive control of the plant. The scheme is tested with set-point tracking and disturbance rejection problems on the plant while control performance is compared with that of PI controllers, a simplified mechanistic model-based NMPC developed in previous work and a linear model predictive controller (LMPC). Results show significant improvements in control performance by the new parallel NMPC-PI control scheme. en_UK
dc.language.iso en_UK en_UK
dc.publisher Elsevier Science B.V., Amsterdam. en_UK
dc.rights “NOTICE: this is the author’s version of a work that was accepted for publication in Control Engineering Practice. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Control Engineering Practice, Volume 18, Issue 12, December 2010, Pages 1418-1428 DOI10.1016/j.conengprac.2010.08.002”
dc.subject Multiple-effect evaporators Nonlinear model predictive control Nonlinear system identification Recurrent neural networks Automatic differentiation recurrent neural-networks automatic differentiation multivariable processes system-identification models reactor backpropagation temperature inverse time en_UK
dc.title Identification and predictive control of a multistage evaporator en_UK
dc.type Article en_UK


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