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  • Since their discovery, fermentation processes have gone along not only with the industrial beverages production and breweries but since the times of Alexander Fleming they have become a crucial part of the health care due to antibiotics production (from which the overwhelming majority of 90% is produced during a fermentation process). However, complicated dynamics and strong nonlinearities cause that the production with the use of linear control methods achieves only suboptimal yields. From the variety of nonlinear approaches, gradient method has proved the ability to handle these issues - nevertheless, its potential in the field of fermentation processes has not been revealed completely. In this paper, two fresh control strategies are introduced and compared - both of them are based on a double-input optimization approach, yet a successful reduction to a single-input optimization task is proposed. To accomplish this, model structure used in the previous work has been modified so that it corresponds with the new optimization strategies which together with the model stands for the main contribution of this paper.
  • Since their discovery, fermentation processes have gone along not only with the industrial beverages production and breweries but since the times of Alexander Fleming they have become a crucial part of the health care due to antibiotics production (from which the overwhelming majority of 90% is produced during a fermentation process). However, complicated dynamics and strong nonlinearities cause that the production with the use of linear control methods achieves only suboptimal yields. From the variety of nonlinear approaches, gradient method has proved the ability to handle these issues - nevertheless, its potential in the field of fermentation processes has not been revealed completely. In this paper, two fresh control strategies are introduced and compared - both of them are based on a double-input optimization approach, yet a successful reduction to a single-input optimization task is proposed. To accomplish this, model structure used in the previous work has been modified so that it corresponds with the new optimization strategies which together with the model stands for the main contribution of this paper. (en)
Title
  • Gradient method optimization of penicillin production: new strategies
  • Gradient method optimization of penicillin production: new strategies (en)
skos:prefLabel
  • Gradient method optimization of penicillin production: new strategies
  • Gradient method optimization of penicillin production: new strategies (en)
skos:notation
  • RIV/68407700:21230/12:00195253!RIV13-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 138356
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/12:00195253
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Fermentation process; penicillin; gradient method; optimization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [04CDCD503097]
http://linked.open...v/mistoKonaniAkce
  • Barcelona
http://linked.open...i/riv/mistoVydani
  • Barcelona
http://linked.open...i/riv/nazevZdroje
  • 2012 20th Mediterranean Conference on Control & Automation (MED 2012)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Čelikovský, Sergej
  • Pčolka, Matej
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/MED.2012.6265808
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-1-4673-2530-1
http://localhost/t...ganizacniJednotka
  • 21230
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