Improvement of the robustness of model-based measuring methods using fuzzylogic

In order to provide monitoring and diagnosis of the actual complete process state during both normal operation and accidental conditions, model-based measuring methods are applied as analytical redundancy in addition to or in stead of existing hardware redundancies. Regarding the improvement of robus tness of classical model-based measuring methods, the combination of model- and knowledge-based algorithms in the form of hybrid methods is proposed. This paper presents different kinds of developed hybrid methods which suppo rt the classical model-based measuring methods (observer) by fuzzy algorith ms. The fuzzy controllers adapt or describe several parameters of the obser ver algorithm. Certain advantages of hybrid methods in comparison to classi cal model-based measuring methods are demonstrated. Subject of investigatio n is the determination of the collapsed and the mixture level within pressu re vessels under two-phase flow conditions during accidental depressurizati ons.