Combination of cascade and feed-forward constrained control for stable partial nitritation with biomass retention

TitleCombination of cascade and feed-forward constrained control for stable partial nitritation with biomass retention
Publication TypeJournal Article
Year of Publication2020
AuthorsJamilis M, Garelli F, De Battista H, Volcke EIP
JournalJournal of Process Control
Volume95
Pagination55-66
Date Published09/2020
Abstract

Ammonium removal is a key step in wastewater treatment which can be accomplished biologically. An
interesting process option for this purpose is coupling partial nitritation with the Anammox process.
The goal of the partial nitritation process is to convert half of the ammonium in the influent stream into
nitrite, so both can be later converted into dinitrogen gas by the Anammox reaction. To obtain a stable
partial nitritation, ammonium oxidizing bacteria (AOB) have to prevail over nitrite oxidizing bacteria
(NOB) so as to avoid further conversion of nitrite into nitrate. The dissolved oxygen concentration
is a key variable for the functional group selection. In this study, a constrained combination of
cascade and feedforward control is proposed for reactors with biomass retention, aimed at suppressing
unwanted NOB while keeping a nitrite:ammonium ratio suitable for coupling with Anammox. The
master controller, aimed to regulate this effluent ratio, generates the set-point for the dissolved oxygen
concentration slave controller. In addition to the cascade controller feedback loop, a feed-forward
controller calculates the optimal dissolved oxygen concentration based on the current influent stream
flow rate and concentrations. The resulting dissolved oxygen concentration set-point is compared to
constraints that guarantee the suppression of NOB and survival of AOB. The proposed control strategy is
simple to apply in common wastewater treatment plants with biomass retention. A sensitivity analysis
is performed to assess the effect of model parameters uncertainty on the controller constraints and
to determine which parameters need to be identified with more precision to avoid instability or poor
results. The performance and the effect of the uncertainty of the most sensitive parameters on the
proposed control algorithm are assessed through simulation using realistic streams as inputs of the
process.

URLhttps://authors.elsevier.com/a/1bq0j3Q5WJJ30M
DOI10.1016/j.jprocont.2020.09.002
Research Line: 
Control de sistemas y procesos biológicos
Control of biological processes and systems
Control and monitoring of bioprocesses
Control y monitoreo de bioprocesos