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Modeling, simulation and adaptive process control of biotechnological processes in decentralized anaerobic treatment of domestic wastewater
Author(s) -
VegaDe Lille Marisela,
Groß Frauke,
Delgado Antonio
Publication year - 2014
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201410427
Subject(s) - anammox , anaerobic digestion , sewage treatment , process (computing) , computer science , wastewater , biochemical engineering , process control , process engineering , control engineering , engineering , waste management , chemistry , nitrogen , operating system , denitrifying bacteria , organic chemistry , methane , denitrification
Control in anaerobic wastewater treatment plants is difficult to achieve but necessary due to a high sensitivity to disturbances and process complexity. With the help of different mathematical tools, control strategies can be developed. Particularly, a well‐defined mathematical model can be highly effective for design, assessment and optimization of treatment plants. However, applications directly in the control system of a treatment plant are hard to achieve due to model complexity and usually require specialized software and the engagement of experts in the subject. The objective of the present study was the development of less empirical methods for assessment and control of a decentralized anaerobic plant for the treatment of domestic wastewater. A lab‐scale plant, which consisted of a two‐stage anaerobic digestion process followed by an anaerobic ammonium oxidation (ANAMMOX) reactor for nitrogen removal, was used as object of study. Ordinary differential equation models were implemented to simulate the processes that took place in the treatment plant. With the help of the implemented models, control tools were developed. These tools include a standalone application for monitoring of the two‐stage anaerobic digestion process and an ammonium estimator for the ANAMMOX reactor by means of artificial neural networks (ANNs). The procedures followed aimed to reduce the amount of experimental work required so they can be easily transferred from laboratory to full‐scale conditions. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)