IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i16p1947-d614673.html
   My bibliography  Save this article

Multi-Output Soft Sensor with a Multivariate Filter That Predicts Errors Applied to an Industrial Reactive Distillation Process

Author

Listed:
  • Vladimir Klimchenko

    (Process Control Laboratory, Institute of Automation and Control Process FEB RAS, 5 Radio Str., Vladivostok 690041, Russia)

  • Andrei Torgashov

    (Process Control Laboratory, Institute of Automation and Control Process FEB RAS, 5 Radio Str., Vladivostok 690041, Russia)

  • Yuri A. W. Shardt

    (Department of Automation Engineering, Technical University of Ilmenau, 99084 Ilmenau, Germany)

  • Fan Yang

    (Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China)

Abstract

The paper deals with the problem of developing a multi-output soft sensor for the industrial reactive distillation process of methyl tert-butyl ether production. Unlike the existing soft sensor approaches, this paper proposes using a soft sensor with filters to predict model errors, which are then taken into account as corrections in the final predictions of outputs. The decomposition of the problem of optimal estimation of time delays is proposed for each input of the soft sensor. Using the proposed approach to predict the concentrations of methyl sec-butyl ether, methanol, and the sum of dimers and trimers of isobutylene in the output product in a reactive distillation column was shown to improve the results by 32%, 67%, and 9.5%, respectively.

Suggested Citation

  • Vladimir Klimchenko & Andrei Torgashov & Yuri A. W. Shardt & Fan Yang, 2021. "Multi-Output Soft Sensor with a Multivariate Filter That Predicts Errors Applied to an Industrial Reactive Distillation Process," Mathematics, MDPI, vol. 9(16), pages 1-14, August.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:16:p:1947-:d:614673
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/16/1947/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/16/1947/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marsaglia, George & Tsang, Wai Wan & Wang, Jingbo, 2003. "Evaluating Kolmogorov's Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i18).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
    2. Fernández de Marcos Giménez de los Galanes, Alberto, 2022. "Data-driven stabilizations of goodness-of-fit tests," DES - Working Papers. Statistics and Econometrics. WS 35324, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Sloot Henrik, 2022. "Implementing Markovian models for extendible Marshall–Olkin distributions," Dependence Modeling, De Gruyter, vol. 10(1), pages 308-343, January.
    4. Tatjana Miljkovic & Saleem Shaik & Dragan Miljkovic, 2017. "Redefining standards for body mass index of the US population based on BRFSS data using mixtures," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 197-211, January.
    5. Jos'e Miguel Flores-Contr'o, 2024. "The Gerber-Shiu Expected Discounted Penalty Function: An Application to Poverty Trapping," Papers 2402.11715, arXiv.org, revised Sep 2024.
    6. Steland, Ansgar, 2020. "Testing and estimating change-points in the covariance matrix of a high-dimensional time series," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
    7. Enrique Garcia Tejeda, 2022. "La concentracion espacial de los reportes de disparos al 911 en la Ciudad de Mexico: ¿Comportamiento racional en el uso de armas durante la pandemia Covid-19?," Sobre México. Revista de Economía, Sobre México. Temas en economía, vol. 3(5), pages 69-93.
    8. Carvalho, Luis, 2015. "An Improved Evaluation of Kolmogorovs Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(c03).
    9. Guillaume Coqueret, 2016. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02088097, HAL.
    10. Hui Xuan Tan & Ephrance Abu Ujum & Kwai Fatt Choong & Kuru Ratnavelu, 2015. "Impact analysis of domestic and international research collaborations: a Malaysian case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 885-904, January.
    11. Fernández-de-Marcos, Alberto & García-Portugués, Eduardo, 2023. "Data-driven stabilizations of goodness-of-fit tests," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    12. Steven E. Pav, 2014. "Bounds on Portfolio Quality," Papers 1409.5936, arXiv.org.
    13. Ghosh, Sayantan & Manimaran, P. & Panigrahi, Prasanta K., 2011. "Characterizing multi-scale self-similar behavior and non-statistical properties of fluctuations in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4304-4316.
    14. Nayara Luiz Pires & Daphne Heloisa de Freitas Muniz & Tiago Borges Kisaka & Nathan De Castro Soares Simplicio & Lilian Bortoluzzi & Jorge Enoch Furquim Werneck Lima & Eduardo Cyrino Oliveira-Filho, 2015. "Impacts of the Urbanization Process on Water Quality of Brazilian Savanna Rivers: The Case of Preto River in Formosa, Goiás State, Brazil," IJERPH, MDPI, vol. 12(9), pages 1-16, August.
    15. Guillaume Coqueret, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02000726, HAL.
    16. Song-Hee Kim & Ward Whitt, 2014. "Are Call Center and Hospital Arrivals Well Modeled by Nonhomogeneous Poisson Processes?," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 464-480, July.
    17. Goldman, Matt & Kaplan, David M., 2018. "Comparing distributions by multiple testing across quantiles or CDF values," Journal of Econometrics, Elsevier, vol. 206(1), pages 143-166.
    18. Buschmann, Christoph & Lotze-Campen, Hermann & Rolinski, Susanne & Biewald, Anne, 2015. "A model-based economic assessment of future climate variability impacts on global agricultural markets," 2015 Conference, August 9-14, 2015, Milan, Italy 211377, International Association of Agricultural Economists.
    19. Jonathan J Hunt & Peter Dayan & Geoffrey J Goodhill, 2013. "Sparse Coding Can Predict Primary Visual Cortex Receptive Field Changes Induced by Abnormal Visual Input," PLOS Computational Biology, Public Library of Science, vol. 9(5), pages 1-17, May.
    20. Tamsin Doll & Joshua Moore & Ahmad H Shihab & Bernardo T Lopes & Ashkan Eliasy & Osama Maklad & Richard Wu & Lynn White & Steve Jones & Ahmed Elsheikh & Ahmed Abass, 2020. "Which feature influences on-eye power change of soft toric contact lenses: Design or corneal shape?," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-23, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:16:p:1947-:d:614673. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.