Open AccessCover Feature: Parameter and state estimation of backers yeast cultivation with a gas sensor array and unscented Kalman filter
Author(s) -
YousefiDarani Abdolrahimahim,
PaquetDurand Olivier,
Hinrichs Jörg,
Hitzmann Bernd
Publication year - 2021
Publication title -
engineering in life sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 57
eISSN - 1618-2863
pISSN - 1618-0240
DOI - 10.1002/elsc.202170028
Subject(s) - kalman filter , software , soft sensor , process (computing) , bioreactor , extended kalman filter , computer science , process engineering , real time computing , control engineering , engineering , control theory (sociology) , control (management) , artificial intelligence , chemistry , programming language , operating system , organic chemistry
DOI: 10.1002/elsc.202000058 Successful operation, control and optimization of biotechnological process depend on reliable real‐time available measurements of the process variables. Although some hardware sensors are readily available, they often have several drawbacks: cost, sample destruction, discrete‐time measurements, processing delay, sterilization, disturbances in the hydrodynamic conditions inside the bioreactor, etc. It is therefore of interest to use software sensors [29, 30]. The central idea behind a soft sensor is to use easily accessible on‐line data for the estimation of other process variables that are either difficult to measure or only measured at low frequency [30]. The figure illustrates a software sensor for on‐line monitoring of substrate and biomass production in backers yeast cultivation. For details see article DOI 10.1002/elsc.202000058 on page 169.