State estimation for large-scale wastewater treatment plants

Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based state estimation can provide estimates of the unknown states and increase the reliabili...

Full description

Saved in:
Bibliographic Details
Published inWater research (Oxford) Vol. 47; no. 13; pp. 4774 - 4787
Main Authors Busch, Jan, Elixmann, David, Kühl, Peter, Gerkens, Carine, Schlöder, Johannes P., Bock, Hans G., Marquardt, Wolfgang
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 01.09.2013
Elsevier
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based state estimation can provide estimates of the unknown states and increase the reliability of measurements. In this paper, an integrated approach is presented for the optimization-based sensor network design and the estimation problem. Using the ASM1 model in the reference scenario BSM1, a cost-optimal sensor network is designed and the prominent estimators EKF and MHE are evaluated. Very good estimation results for the system comprising 78 states are found requiring sensor networks of only moderate complexity. •We investigate the choice of sensors and estimators for model-based WWTP control.•An integrated approach to sensor network and estimator design is presented.•Minimum-cost sensor networks are designed that yield fully observable plant models.•Observability of the wastewater feed concentrations is verified as well.•EKF and MHE estimators are applied to the BSM1 benchmark, giving good performance.
Bibliography:http://dx.doi.org/10.1016/j.watres.2013.04.007
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0043-1354
1879-2448
DOI:10.1016/j.watres.2013.04.007