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Software sensors for Monitoring of Biopolymer Production

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F21%3A43923546" target="_blank" >RIV/60461373:22340/21:43923546 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/9447540" target="_blank" >https://ieeexplore.ieee.org/document/9447540</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/PC52310.2021.9447540" target="_blank" >10.1109/PC52310.2021.9447540</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Software sensors for Monitoring of Biopolymer Production

  • Original language description

    The topic of this paper is the design of software sensors for online monitoring of the biotechnological process of biopolymer production, in which biopolymers are accumulated in bacteria as an intracellular energy storage material. The proposed software sensors enabling on-line estimation of the biopolymer concentration represent in the case of these complicated bioprocesses an interesting alternative to the traditional off-line analytical techniques, which have only limited applicability for the real-time control of these bioprocesses. Due to the complexity of biochemical reactions, which make it difficult to create reasonably complex and therefore practically applicable first-principle mathematical models, a data-driven approach to the design of software sensors has been chosen in the presented study. Thus, regression methods were used in the design of the proposed software sensors, including multivariate statistical methods (PLS, PCR), which enabled the creation of software sensors using historical process data. The so obtained software sensors enable not only on-line estimation of the biopolymer concentration, but also the concentration of the cell biomass of the production bacterial culture. The model process for this study was fed-batch cultivation of the Pseudomonas putida KT2442 strain used for the production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs).

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 2021 23rd International Conference on Process Control (PC)

  • ISBN

    978-1-66540-330-6

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    308-312

  • Publisher name

    Czechoslovakia Section IEEE

  • Place of publication

    Praha

  • Event location

    Štrbské Pleso

  • Event date

    Jun 1, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000723653400052