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 (e.g. fuzzy logic (FL) controller) is not useful because of the rather high design effort and the low transparency of its complex structure. A more suitable hierarchical FL-based supervisory control concept is proposed in this paper. 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 situation in terms of the available process sensor signals and activates dynamically the appropriate situation specific low-level controllers. The generic concept of the FL supervisory controller which comprises both a FL process diagnosis and a control mode selection as well as experiences with the industrial application will be presented in this paper.