A neuro-fuzzy supervisory control system for industrial batch processes

The automation of complex industrial batch processes is a difficult problem due to the extremely nonlinear and variable system behavior or the conflicting goals within the different process phases. The introduction of a single multiple-input multiple-output controller is not useful because of the rather high design effort and the low transparency of its complex structure. A more suitable hierarchical fuzzy-logic (FL) based supervisory control concept is proposed. It permits the decomposition of the complex control problem into a series of smaller and simpler ones. In the upper level of the hierarchy the FL-based supervisory controller classifies the actual process phase in terms of the available process sensor signals and activates dynamically the appropriate situation specific low-level controllers. The paper presents the generic concept of the FL supervisory controller that comprises both a FL process diagnosis and a control mode selection as well as experiences with the industrial application