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Optimal Control of Batch Processes Using Particle Swam Optimisation with Stacked Neural Network Models

Lookup NU author(s): Fernando Herrera Elizalde, Dr Jie ZhangORCiD

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Abstract

An optimal control strategy for batch processes using particle swam optimisation (PSO) and stacked neural networks is presented in this paper. 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 penalise wide model prediction confidence bounds. PSO 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.

Publication metadata

Author(s): Herrera F; Zhang J

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computers & Chemical Engineering: 18th European Symposium on Computer Aided Process Engineering (ESCAPE)

Year of Conference: 2008

Pages: 375-380

ISSN: 0098-1354

Publisher: Pergamon

URL: http://dx.doi.org/10.1016/j.compchemeng.2009.01.009

DOI: 10.1016/j.compchemeng.2009.01.009

Library holdings: Search Newcastle University Library for this item

ISBN: 18734375

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