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Feedback identification of continuous microbial growth systems
Author(s) -
O'Neil D. G.,
Lyberatos G.
Publication year - 1986
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.260280907
Subject(s) - chemostat , identification (biology) , computer science , nonlinear system , process (computing) , system identification , control theory (sociology) , forcing (mathematics) , bifurcation , system dynamics , biological system , control (management) , biochemical engineering , control engineering , mathematics , artificial intelligence , engineering , data modeling , biology , ecology , mathematical analysis , genetics , physics , quantum mechanics , database , bacteria , operating system
The fundamental problem of dynamic modeling of continuous culture systems for process control and optimization is addressed. Forcing a system to bifurcation via feedback control is a very promising method for model discrimination and identification. Dynamic information is obtained by using this technique, the dynamic behavior of the chemostat as predicted by unstructured models, the model with delay, and a structured model has been analyzed. The method exposes significant differences in the nonlinear dynamic structure of the various models and can be implemented to discriminate between various possible models for a continuous culture system.