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Lookup NU author(s): Dr Dominic Searson, Dr Mark Willis, Professor Allen Wright
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This article aims to demonstrate the potential of the S-system methodology to construct hybrid models of fed-batch reaction systems in which both the reaction network equations and kinetic parameters are unknown. Furthermore, the article aims to show that the hybrid S-systems models can be used as an aid in the inference of the structure of unknown reaction networks from simple fed-batch experimental data and very limited a priori knowledge of the products and reactants. The concept of S-systems is that of a power law formalism for the canonical approximate representation of dynamic non-linear systems. This formalism, which has origins in biochemical systems theory (BST), has the useful property that the causal structure of a network is dictated by the values of its parameters and so network inference problems (e.g. elucidating the topology of a network of reactive species) can be recast as parameter estimation problems. This methodology has been applied in a number of biological fields including metabolic pathway analysis and the inference of gene regulatory networks. Here, the methodology is adapted as a hybrid modelling tool to aid the structural identification of chemical reaction networks in fed-batch reactors. The principle of the approach is demonstrated with simulated noisy data from fed-batch experiments using a reaction network consisting of 5 chemical species and 4 elementary reactions. A co-evolutionary algorithm (comprising binary and real valued components) is used to evolve the topology and the parameter values of the S-system equations concurrently. Unlike many other hybrid modelling approaches, these S-system equations can then be interpreted in order to construct a cause and effect network diagram that accurately reflects the underlying chemical reaction network.
Author(s): Searson, D. P., Willis, M. J., Home, S., Wright, A. R.
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: CHISA 2006: 17th International Congress of Chemical and Process Engineering
Year of Conference: 2006
Publisher: Czech Society of Chemical Engineering
Library holdings: Search Newcastle University Library for this item
ISBN: 8086059456
