NDLI: Systematic simplification methodology applied to an activated sludge reactor model

Content Provider	IEEE Xplore Digital Library
Author	Aouaouda, S. Khadir, M.T. Mourot, G. Ragot, J.
Copyright Year	2011
Description	Author affiliation: Centre de Recherche en Automatique de Nancy, Nancy Université, 2, avenue de la Foret de Haye, 54516 Vandoeuvre-lès-Nancy Cedex France (Mourot, G.; Ragot, J.) \|\| Laboratory of Research in Informatics, Annaba University, BP 12, 23200 Sidi-Amar, Algeria (Aouaouda, S.; Khadir, M.T.)
Abstract	This article proposes a linearization technique for an activated sludge reactor model. Starting with a reduced model using three state variables related to the organic substrate, biomass and oxygen concentrations; the linearization approach is developed and validated. In a first step, sensitivity analysis is used to evaluate the model output sensitivity to changes with respect to the model input variables. The input variables identified as non-influent, can then be discarded, leading to a model simplification. In a second step, locally valid linear model are derived. The linearization is based on approximation of nonlinear terms by linear combinations of variables of interest. In the third step the unknown parameters in the linear terms are identified using an evolutionary algorithm. The main advantage of the proposed strategy is that it conserves the global structure of the original model. The obtained linear model allows easier studies of the state estimation and control schemes problems.
Starting Page	143
Ending Page	146
File Size	536899
Page Count	4
File Format	PDF
ISBN	9781457706899
e-ISBN	9781457706905
DOI	10.1109/WOSSPA.2011.5931435
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-09
Publisher Place	Algeria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Analytical models Sensitivity analysis Biological system modeling Mathematical model Indexes Inductors
Content Type	Text
Resource Type	Article

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