Title: Model reduction and identification for temperature control of the phenol-formaldehyde reaction in batch reactors
Authors: Francesco Pierri, Mario Iamarino, Fabrizio Caccavale, Vincenzo Tufano
Addresses: Dipartimento di Ingegneria e Fisica dell'Ambiente, Universita degli Studi della Basilicata, Via dell'Ateneo Lucano 10, 85100 Potenza, Italy. ' Dipartimento di Ingegneria e Fisica dell'Ambiente, Universita degli Studi della Basilicata, Via dell'Ateneo Lucano 10, 85100 Potenza, Italy. ' Dipartimento di Ingegneria e Fisica dell'Ambiente, Universita degli Studi della Basilicata, Via dell'Ateneo Lucano 10, 85100 Potenza, Italy. ' Dipartimento di Ingegneria e Fisica dell'Ambiente, Universita degli Studi della Basilicata, Via dell'Ateneo Lucano 10, 85100 Potenza, Italy
Abstract: This study provides an overall strategy for building an effective model-based control scheme for the highly exothermic phenol-formaldehyde reaction for the production of 1,3,5-methylolphenol, a phenolic resin precursor, carried out in a jacketed batch reactor. A simplified representation of the reactive system is proposed by means of reduced kinetic models, whose unknown parameters are identified with a two-step procedure. The experimental data, used for model identification, have been simulated using a complex reaction network, involving large number of reactions and compounds. The proposed simplified models are adopted to design a model-based feedback control scheme for the temperature control in a batch reactor. The obtained performance is tested in simulation and compared to those obtained via a classical PID controller. According to simulations, it can be stated that the model-based controller always achieves the best performance with respect to the PID controller and the robustness of the control scheme suggests the use of the simplest reduced model without significative performance degradation.
Keywords: model reduction; parameters identification; model-based control; temperature control; phenol-formaldehyde reaction; batch reactors; kinetic modelling; feedback control; PID control; simulation.
DOI: 10.1504/IJMIC.2011.041783
International Journal of Modelling, Identification and Control, 2011 Vol.13 No.4, pp.278 - 290
Published online: 21 Mar 2015 *
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