Advanced
control of wastewater treatment plants |
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My contribution in this European-founded project has been
the development of software sensors in the water line of a
waste water treatment plants (WWTPs), which serves for
monitoring the ammonia concentrations in the aerobic tanks
of the plant line and in the anoxic tank. In addition, the
software sensor serves to track the maximum nitrification
rate. Specifically, Extended Kalman filter is derived and
shown the Kalman filter to a much broader class of
non-Gaussian distributions. The filter has several desirable
properties, such as its ability to preserve statistical
relationships in the prior state and converge to highly
accurate observations [1]. |
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Some projects
in this field where I have been working on: |
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DARROW -
Making wastewater treatment more sustainable and efficient
using a data-driven AI solution |
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DARROW aims to build a data-driven AI solution to optimise
resource recovery from wastewater by making wastewater
treatment plants more autonomous and energy efficient.
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Award Institution: European Union’s Horizon Europe research
and innovation programme within the project DARROW (grant
agreement Nº 101070080)
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Process covariance matrix [1] |
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Kalman gain values during convergence for state model
covariance [1] |
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Proposed methodology for the application of the extended
Kalman filter [1] |
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References: |
[1] Ricardo
Rodríguez Jorge, A
grey-box model for real-time control and monitoring , Lecture
Notes in Networks and Systems - Proceedings of the The 19th
International Conference on P2P, Parallel, Grid, Cloud and
Internet Computing (3PGCIC-2024, Springer Nature Switzerland
AG, San Benedetto del Tronto, Italy, November-13-15, 2024 (Web
of Sciences, SCOPUS).
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[2] Cristina Rodríguez-García, Cesar Arenas, Saioa
Arrizabalaga, Luis V. Varcárcel, Ricardo
Rodríguez-Jorge,
Itxaro Errandonea, Decision
support tool for WWTP operations: DARROW project case study,
Poster, en: Book of Abstracts. IWA Young Water Professionals
Spain Conference 2024. |
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