A linear ASM1 based multi-model for activated sludge systems
Authors:
Ilse Smets a;
Liesbeth Verdickt a;
Jan Van Impe a
| Affiliation: | a BioTeC - Bioprocess Technology and Control, Katholieke Universiteit Leuven, Heverlee, Belgium |
DOI:
10.1080/13873950600723467
Publication Frequency:
6 issues per year
Published in:
Mathematical and Computer Modelling of Dynamical Systems,
Volume
12,
Issue
5
October
2006
, pages 489
- 503
Subjects:
Analysis - Mathematics;
Applied Mechanics;
Dynamical Control Systems;
Dynamical Systems;
Mathematical Modelling;
Mathematics & Statistics for Engineers;
Simulation & Modeling;
Formats available:
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(English)
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(English)
Previously published as:
Mathematical Modelling of Systems
(1381-2424)
until 1998
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Abstract
In the search for a reliable but simple model for the biodegradation processes of an activated sludge wastewater treatment plant, this paper presents a multi-model which is valid for the global operating region of a standard carbon and nitrogen removing facility. In a first step, locally valid linear models are derived. Two linearization procedures are compared. The first procedure is the classical Taylor series expansion, while the second is a newly developed linearization procedure based on weighted linear combinations. In a second step, the locally valid models are combined to obtain one globally valid multi-model. Previous work has focused on the most basic configuration of one anoxic and one aerated tank followed by a point settler [Smets, I.Y., Haegebaert, J.V. and Carrette, R. and Van Impe, J.F., 2003, Water Research, 37, 1831 - 1851]. Refinements to the methodology are however needed (and presented here) once the influent flow rate range is increased and the benchmark configuration, proposed by the COST 682 working group no. 2, is taken as the simulation protocol. The main advantage of the obtained linear model (structure) remains the alliance of high predictive power with low complexity, rendering the multi-model fit for on-line optimization and control schemes.
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| Keywords: ASM1; Model complexity reduction; Linearization; COST benchmark |
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