Estimación de la producción de microalgas en fotobiorreactores industriales

  1. Delgado, Emma 1
  2. Rodríguez Miranda, Enrique 2
  3. Baños, Alfonso 3
  4. Barreiro, Antonio 1
  5. Moreno Úbeda, José Carlos 2
  6. Guzmán, José Luis 2
  1. 1 Universidade de Vigo
    info

    Universidade de Vigo

    Vigo, España

    ROR https://ror.org/05rdf8595

  2. 2 Universidad de Almería
    info

    Universidad de Almería

    Almería, España

    ROR https://ror.org/003d3xx08

  3. 3 Universidad de Murcia
    info

    Universidad de Murcia

    Murcia, España

    ROR https://ror.org/03p3aeb86

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Llibre:
XLIV Jornadas de Automática: libro de actas: Universidad de Zaragoza, Escuela de Ingeniería y Arquitectura, 6, 7 y 8 de septiembre de 2023, Zaragoza
  1. Ramón Costa Castelló (coord.)
  2. Manuel Gil Ortega (coord.)
  3. Óscar Reinoso García (coord.)
  4. Luis Enrique Montano Gella (coord.)
  5. Carlos Vilas Fernández (coord.)
  6. Elisabet Estévez Estévez (coord.)
  7. Eduardo Rocón de Lima (coord.)
  8. David Muñoz de la Peña Sequedo (coord.)
  9. José Manuel Andújar Márquez (coord.)
  10. Luis Payá Castelló (coord.)
  11. Alejandro Mosteo Chagoyen (coord.)
  12. Raúl Marín Prades (coord.)
  13. Vanesa Loureiro-Vázquez (coord.)
  14. Pedro Jesús Cabrera Santana (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 9788497498609

Any de publicació: 2023

Pàgines: 295-299

Congrés: Jornadas de Automática (44. 2023. Zaragoza)

Tipus: Aportació congrés

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Resum

Microalgae reactors provide an efficient and clean alternative for production of biogas, biofuel, nutritional and cosmetic products, etc. The main control objective in these systems is the optimization of productivity. For this reason, it is crucial monitoring the biomass concentration in the reactor and so to determine the productivity in real time. Despite this, there are no sufficiently robust solutions on the market, especially for open reactors on an industrial scale. This paper presents the first results in the development of a new online biomass estimator, based on a very robust observer, the sliding modes observer , combined with a nonlinear and time-varying dynamic model endowed with a minimum number of states, which allow capturing the essential aspects of the microalgae production process. This soft-sensor has been tested with a complete model of the reactor and the simulations show promising results in terms of accuracy and robustness.

Fuente de los datos: Dialnet