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Robust adaptive predictive control of the dissolved gaseous environment of submerged microbial processes
Author(s) -
Diaz Constantino,
Dieu Pierre,
Lelong Philippe,
Feuillerat Claude,
Salome Marc
Publication year - 1998
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/(sici)1099-1115(199806)12:4<347::aid-acs495>3.0.co;2-9
Subject(s) - model predictive control , controller (irrigation) , bioreactor , process engineering , computer science , volumetric flow rate , control engineering , adaptive control , control theory (sociology) , environmental science , control (management) , engineering , chemistry , artificial intelligence , physics , biology , organic chemistry , quantum mechanics , agronomy
The partial pressures of dissolved oxygen (pO 2 ) and of dissolved carbon dioxide (pCO 2 ) in laboratory‐scale bioreactors cannot be effectively controlled by conventional controllers because of the constantly changing dynamics of the fed‐batch processes, the large variety of the micro‐organisms to be tested and the disturbances encountered during cultures. A strategy using a decentralized control of the pO 2 by the agitation rate and of the pCO 2 by the air flow rate has been developed. Each controller is made of an adaptive predictive algorithm based on the Generalized Predictive Control, and uses a strategy driver to gradually update its smoothness along the fed‐batch. This totally decentralized control strategy of a partially coupled multi‐variable non‐linear system has been implemented on a PC computer and connected to the existing hardware without modifications. It needs no manual tuning and has been successfully used with various microorganisms despite numerous environmental disturbances. © 1998 John Wiley & Sons, Ltd.