FN Archimer Export Format
PT J
TI About frame estimation of growth functions and robust prediction in bioprocess modeling
BT 
AF KRICHEN, Emna
   RAPAPORT, A.
   FOUILLAND, Eric
AS 1:1,2;2:3;3:2;
FF 1:;2:;3:;
C1 Univ Montpellier, INRA, SupAgro, MISTEA, Montpellier, France.
   Univ Montpellier, IFREMER, CNRS, IRD,MARBEC, Montpellier, France.
   Univ Montpellier, INRA, SupAgro, MISTEA, Montpellier, France.
C2 MONTPELLIER SUPAGRO, FRANCE
   CNRS, FRANCE
   INRA, FRANCE
UM MARBEC
IN WOS Cotutelle UMR
   copubli-france
IF 3.666
TC 0
UR https://archimer.ifremer.fr/doc/00609/72149/73205.pdf
LA English
DT Article
DE ;Functional estimation;Interval observers;Growth functions;Least square
AB We address the problem of determining functional framing from experimental data points in view of robust time-varying predictions, which is of crucial importance in bioprocess monitoring. We propose a method that provides guaranteed functional bounds, instead of sets of parameters values for growth functions such as the classical Monod or Haldane functions commonly used in bioprocess modeling. We illustrate the applicability of the method with bioreactor simulations in batch and continuous mode, as well as on real data. We also present two extensions of the method adding flexibility in its application, and discuss its efficiency in providing guaranteed state estimations. 
PY 2020
PD JAN
SO Journal Of Process Control
SN 0959-1524
PU Elsevier Sci Ltd
VL 85
UT 000510953100011
BP 121
EP 135
DI 10.1016/j.jprocont.2019.11.009
ID 72149
ER

EF