Intelligent supervisory systems for industrial process control

This paper presents a supervisory control scheme based on the hybrid systems theory and fuzzy events detection approach presented in [1]. The fuzzy event detector is a linguistic model, which synthesizes complex relations between process variables and process events incorporating experts' knowledge about the process operation. The detection feature allows the anticipation of appropriate control actions, which depend upon the selected membership functions used to characterize the process under scrutiny. Additionally, it is also proposed a fuzzy logic based intelligent hierarchical system, which assigns priorities among simultaneous generated events in complex processes. The performance of the suggested scheme is applied to a theoretical evaporation system in terms of computational simulation results.