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|Document Type: ||Article|
|Title: ||Identification and predictive control of a multistage evaporator|
|Authors: ||Atuonwu, J. C.|
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.|
|Appears in Collections:||Staff publications - School of Engineering|
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