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State estimation and nonlinear tracking control simulation approach. Application to a bioethanol production system

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Abstract

Tracking control of specific variables is key to achieve a proper fermentation. This paper analyzes a fed-batch bioethanol production process. For this system, a controller design based on linear algebra is proposed. Moreover, to achieve a reliable control, on-line monitoring of certain variables is needed. In this sense, for unmeasurable variables, state estimators based on Gaussian processes are designed. Cell, ethanol and glycerol concentrations are predicted with only substrates measurement. Simulation results when the controller and estimators are coupled, are shown. Furthermore, the algorithms were tested with parametric uncertainties and disturbances in the control action, and are compared, in all cases, with neural networks estimators (previous work). Bayesian estimators show a performance improvement, which is reflected in a decrease of the total error. Proposed techniques give reliable monitoring and control tools, with a low computational and economic cost, and less mathematical complexity than neural network estimators.

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Acknowledgments

To the National Council of Scientific and Technological Research (CONICET) and the Chemical Engineering Institute (IIQ) from the National University of San Juan for their support in this investigation.

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Authors and Affiliations

  1. Instituto de Ingeniería Química, Universidad Nacional de San Juan (UNSJ), CONICET, Av. Lib. San Martín Oeste 1109, J5400ARL, San Juan, Argentina

    M. Cecilia Fernández, M. Nadia Pantano, Leandro Rodriguez & Gustavo Scaglia

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  1. M. Cecilia Fernández
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  2. M. Nadia Pantano
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  3. Leandro Rodriguez
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  4. Gustavo Scaglia
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Correspondence to M. Cecilia Fernández.

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Fernández, M.C., Pantano, M.N., Rodriguez, L. et al. State estimation and nonlinear tracking control simulation approach. Application to a bioethanol production system. Bioprocess Biosyst Eng 44, 1755–1768 (2021). https://doi.org/10.1007/s00449-021-02558-y

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