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On the applicability of adaptive bioprocess state estimators
Author(s) -
Lant Paul A.,
Tham Ming T.,
Montague Gray A.
Publication year - 1993
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.260421108
Subject(s) - bioprocess , estimator , computer science , process (computing) , selection (genetic algorithm) , identification (biology) , biochemical engineering , mathematical optimization , data mining , industrial engineering , machine learning , engineering , mathematics , statistics , chemical engineering , biology , operating system , botany
This article presents an industrial case study, examining the application of a novel adaptive biomass estimator to an industrial microfungi production process. It is our intention that this contribution should focus upon the implementation issues of the algorithm, in preference to a rigorous theoretical development. The novel algorithm adopted is developed from Adaptive Inferential Estimation studies of Guilandoust and co‐workers. The technique utilizes input–output process measurements obtained at different frequencies, thereby providing more frequent estimates of biomass concentration than are otherwise available from off‐line laboratory analyses. The algorithm is particularly suited to the biotechnology industry, as it is capable of utilizing irregular assay measurements with varying delays. Although this article demonstrates the encouraging industrial implications of the adaptive algorithm, like all adaptive techniques currently developed, it is restricted by the inability to perform robust on‐line system identification. The ultimate selection of a “suboptimal” “fixed parameter” algorithm for on‐line implementation, is therefore directly attributable to these inadequacies. Aspects of data acquisition, data pretreatment, and data quality are critical for real process applications, and while some practical approaches are adopted here, many important implementation problems remain unresolved. © 1993 John Wiley & Sons, Inc.