Integrated operation of Wastewater Treatment Plants is still far from being solved. A reasonable proposal should link advanced and robust control algorithms to some knowledge-based techniques, allocating the detailed engineering to numerical computations, while delegating the logical analysis and reasoning to supervisory intelligent systems. This paper describes the development and implementation of a knowledge-based Hybrid Supervisory System to support the operation of a real Wastewater Treatment Plant. The system integrates different reasoning modules, overcoming the limitations in the use of each single technique, while providing an agent based architecture with additional modularity and independence. It is structured into three separated levels: data gathering, diagnosis, and decision support. The different tasks of the system are performed in a seven-step cycle: data gathering and update, diagnosis, supervision, prediction, communication, actuation, and evaluation phase. In spite of certain reservations of the scientific community about the use of these techniques, the system is successfully performing real-time support to the operation of the Granollers facility since September 1999. Results of the first four-month validation period are shown and discussed. An example of the system behavior is also shown in the paper. The conclusions indicate the key steps which are necessary to transfer the system to another facility.

This content is only available as a PDF.
You do not currently have access to this content.