Quaglio, M; Waldron, C; Pankajakshan, A; Cao, E; Gavriilidis, A; Fraga, ES; Galvanin, F; (2019) An online reparametrisation approach for robust parameter estimation in automated model identification platforms. Computers & Chemical Engineering , 124 pp. 270-284. 10.1016/j.compchemeng.2019.01.010.

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Abstract

Automated model identification platforms were recently employed to identify parametric models online in the course of unmanned experimental campaigns. The algorithms controlling these platforms include two computational elements: i) a tool for parameter estimation; ii) a tool for model-based experimental design. Both tools require the solution of complex optimisation problems and their effective outcome relies on their respective objective functions being well-conditioned. Ill-conditioned objective functions may arise when the model is characterised by a weak parametrisation, i.e. the model parameters are practically non-identifiable and/or extremely correlated. In this work, a robust reparametrisation technique is proposed and tested both in-silico and in an automated model identification platform. The benefit of reparametrisation is demonstrated on a case study for the identification of a kinetic model of catalytic esterification of benzoic acid with ethanol in a flow microreactor.

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