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Anaerobic Digestion Process Control Using a Data-Driven Internal Model Control Method

Author

Listed:
  • Larisa Condrachi

    (Department of Automatic Control and Electrical Engineering, “Dunărea de Jos” University of Galaţi, 47 Domnească 47 Street, 800008 Galaţi, Romania)

  • Ramón Vilanova

    (Department of Telecommunications and Systems Engineering, Universitat Autonoma de Barcelona, 08193 Barcelona, Spain)

  • Montse Meneses

    (Department of Telecommunications and Systems Engineering, Universitat Autonoma de Barcelona, 08193 Barcelona, Spain)

  • Marian Barbu

    (Department of Automatic Control and Electrical Engineering, “Dunărea de Jos” University of Galaţi, 47 Domnească 47 Street, 800008 Galaţi, Romania)

Abstract

Anaerobic digestion processes offer the possibility for wastewater treatment while obtaining a benefit through the obtained biogas. This paper aims to continue the effort to adopt data-driven control methods in the case of anaerobic digestion processes. The paper proposes a data-based Internal Model Control approach applied to an anaerobic digestion process. The paper deals extensively with the issue of choosing the reference model and proposing an engineering approach to this issue. The paper also addresses the issue of verifying robust stability, a very important aspect considering the uncertainties that characterize bioprocesses in general. The approach proposed in the paper is validated through a numerical simulation using the Anaerobic Digestion Model No. 1. During the validation of the proposed control solution, the main operating conditions were analyzed, such as the setpoint tracking performance, the rejection of disturbance generated by variations in the influent concentration, and the effect of the measurement noise on the controlled variable.

Suggested Citation

  • Larisa Condrachi & Ramón Vilanova & Montse Meneses & Marian Barbu, 2021. "Anaerobic Digestion Process Control Using a Data-Driven Internal Model Control Method," Energies, MDPI, vol. 14(20), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6746-:d:658103
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    Citations

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    Cited by:

    1. Damir Vrančić & Paulo Moura Oliveira & Pavol Bisták & Mikuláš Huba, 2023. "Model-Free VRFT-Based Tuning Method for PID Controllers," Mathematics, MDPI, vol. 11(3), pages 1-29, January.
    2. Luis G. Cortés & J. Barbancho & D. F. Larios & J. D. Marin-Batista & A. F. Mohedano & C. Portilla & M. A. de la Rubia, 2022. "Full-Scale Digesters: Model Predictive Control with Online Kinetic Parameter Identification Strategy," Energies, MDPI, vol. 15(22), pages 1-23, November.

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