Design framework for intelligent supervision of industrial processes

Timely faults detection in an industrial process is a key aspect for designing a framework for intelligent supervisory control. A way to perform supervisory control is by providing intelligence to the supervision mechanism in continuous processes exposed to faults in order to cope with the identification of a diversity of faults, classify them and to be able to anticipate the consequences derived by their occurrence. In this article we propose an extension of the multiresolutional models approach to construct a fuzzy logic-agent technology-event detection approaches-based supervisory framework. Also the suggested framework is validated by means of a discrete-event simulation program.