REAL TIME SUPERVISION OF WASTEWATER TREATMENT PLANTS : A DISTRIBUTED AI APPROACH

Authors

Miquel Sànchez-Marrè miquel@lsi.upc.es
Ulises Cortés ia@lsi.upc.es

Departament de Llenguatges i Sistemes Informàtics
Universitat Politècnica de Catalunya
Edifici C5-Campus Nord
C/ Jordi Girona 1-3
08034 Barcelona, Catalonia, Spain

Javier Lafuente lafuente@uab-eq.uab.es

Departament d'Enginyeria Química
Universitat Autònoma de Barcelona
Edifici C
08193 Bellaterra (Barcelona), Catalonia, Spain

Ignasi R-Roda eqairr@fc.udg.es
Manel Poch eqampe@fc.udg.es

Laboratori d'Enginyeria Química i Ambiental.
Facultat de Ciències
Universitat de Girona
Campus de Montilivi
17071 Girona, Catalonia, Spain

Abstract

Conventional automatic control systems applied to wastewater treatment plants deals withs ome difficulties : complexity of the system, an ill - structured domain, qualitative information, uncertainty or approximate knowledge, real-time dynamic system, etc . Also, the knowledge-based approaches developed from artificial intelligence field show other disadvantages : brittleness, knowledge acquisition problem, do not learn from experience, the increasing complexity of the systems, etc. The main goal of the paper is to present a knowledge-based distributed architecture for real time supervision and control of wastewater treatment plants that overcomes some of these troubles. It is discussed the development of the application and the methodology employed in it. The prototype's architecture being developed DAI-DEPUR is detailed together with some obtained results .

Keywords: Real-time Supervision and control, Distributed AI, Knowledge-based Systems, Wastewater treatment, Knowledge Acquisition, Environmental Engineering, Biotechnology

Citation

M. SÓnchez, I. R-Roda, J. Lafuente, U. CortÚs, M. Poch, "Real time supervision of wastewater treatment plants: A distributed approach". 2 IFAC Workshop on Computer Software Structures Integrating AI/KBS (CSI-AI/KBS'94). pp 188-193. Lund, Sweden.

Postscript

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