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Lookup NU author(s): Fernando Herrera Elizalde, Dr Jie ZhangORCiD
An optimal control strategy for batch processes using particle swam optimisation (PSO) and stacked neural networks is presented in this paper. Stacked neural network models are developed from historical process operation data. Stacked neural networks are used to improve model generalisation capability, as well as provide model prediction confidence bounds. In order to improve the reliability of the calculated optimal control policy, an additional term is introduced in the optimisation objective function to penalize wide model prediction confidence bounds. The optimisation problem is solved using PSO, which can cope with multiple local minima and could generally find the global minimum. Application to a simulated fed-batch process demonstrates that the proposed technique is very effective.
Author(s): Herrera F, Zhang J
Publication type: Article
Publication status: Published
Journal: Computers & Chemical Engineering
Year: 2009
Volume: 33
Issue: 10
Pages: 1593-1601
Date deposited: 05/06/2014
ISSN (print): 0098-1354
ISSN (electronic): 1873-4375
Publisher: Pergamon
URL: http://dx.doi.org/10.1016/j.compchemeng.2009.01.009
DOI: 10.1016/j.compchemeng.2009.01.009
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