Modelling of Baker’s Yeast Production

In the present work, parametric models for the control of bioreactor temperature have been applied. Various order discrete time model parameters were evaluated theoretically and experimentally. Two types of input signals were used as external force to determine Auto Regressive Moving Average with Ex...

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Main Authors: Havva Boyacıoğlu, Suna Ertunç, Hale Hapoğlu
Format: Article
Language:English
Published: izzet kara 2017-01-01
Series:International Journal of Secondary Metabolite
Subjects:
Online Access:https://dergipark.org.tr/tr/pub/ijsm/issue/23667/252053?publisher=ijate
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author Havva Boyacıoğlu
Suna Ertunç
Hale Hapoğlu
author_facet Havva Boyacıoğlu
Suna Ertunç
Hale Hapoğlu
author_sort Havva Boyacıoğlu
collection DOAJ
description In the present work, parametric models for the control of bioreactor temperature have been applied. Various order discrete time model parameters were evaluated theoretically and experimentally. Two types of input signals were used as external force to determine Auto Regressive Moving Average with Exogenous (ARMAX) model parameters with Recursive Least Square (RLS) parameter estimation algorithm. The third order ARMAX model is utilized, and compared with the second order one. Ternary and square disturbances are given to the cooling water flow rate which can be chosen as manipulating variable in closed loop cases. System response is monitored continuously and the model parameters are calculated. The models with experimentally identified parameters are compared with ones that their parameters are identified theoretically.
format Article
id doaj-art-85372af891f94986a19a2719e686ec74
institution DOAJ
issn 2148-6905
language English
publishDate 2017-01-01
publisher izzet kara
record_format Article
series International Journal of Secondary Metabolite
spelling doaj-art-85372af891f94986a19a2719e686ec742025-08-20T03:07:09Zengizzet karaInternational Journal of Secondary Metabolite2148-69052017-01-0141101710.21448/ijsm.252053618Modelling of Baker’s Yeast ProductionHavva BoyacıoğluSuna ErtunçHale HapoğluIn the present work, parametric models for the control of bioreactor temperature have been applied. Various order discrete time model parameters were evaluated theoretically and experimentally. Two types of input signals were used as external force to determine Auto Regressive Moving Average with Exogenous (ARMAX) model parameters with Recursive Least Square (RLS) parameter estimation algorithm. The third order ARMAX model is utilized, and compared with the second order one. Ternary and square disturbances are given to the cooling water flow rate which can be chosen as manipulating variable in closed loop cases. System response is monitored continuously and the model parameters are calculated. The models with experimentally identified parameters are compared with ones that their parameters are identified theoretically.https://dergipark.org.tr/tr/pub/ijsm/issue/23667/252053?publisher=ijatebaker’s yeastsystem identificationsaccharomyces cerevisiae as a second metabolite source
spellingShingle Havva Boyacıoğlu
Suna Ertunç
Hale Hapoğlu
Modelling of Baker’s Yeast Production
International Journal of Secondary Metabolite
baker’s yeast
system identification
saccharomyces cerevisiae as a second metabolite source
title Modelling of Baker’s Yeast Production
title_full Modelling of Baker’s Yeast Production
title_fullStr Modelling of Baker’s Yeast Production
title_full_unstemmed Modelling of Baker’s Yeast Production
title_short Modelling of Baker’s Yeast Production
title_sort modelling of baker s yeast production
topic baker’s yeast
system identification
saccharomyces cerevisiae as a second metabolite source
url https://dergipark.org.tr/tr/pub/ijsm/issue/23667/252053?publisher=ijate
work_keys_str_mv AT havvaboyacıoglu modellingofbakersyeastproduction
AT sunaertunc modellingofbakersyeastproduction
AT halehapoglu modellingofbakersyeastproduction