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Please use this identifier to cite or link to this item: http://dspace.lib.cranfield.ac.uk/handle/1826/5215

Document Type: Article
Title: Identification and predictive control of a multistage evaporator
Authors: Atuonwu, J. C.
Cao, Yi
Rangaiah, G. P.
Tade, M. O.
Issue Date: 2010
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
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.
URI: http://dx.doi.org/10.1016/j.conengprac.2010.08.002
http://dspace.lib.cranfield.ac.uk/handle/1826/5215
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