IMPROVEMENT OF THE ROBUSTNESS OF MODEL-BASED MEASURING METHODS USING FUZZY LOGIC

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 instead of existing hardware redundancies. Regarding the improvement of robustness of classical model-based measuring methods, the combination of model- and It Knowledge-based algorithms in the form of hybrid methods is proposed. This paper presents different kinds of developed hybrid methods which support the classical model-based measuring methods (observer) by fuzzy algorithms. The fuzzy controllers adapt or describe several parameters of the observer algorithm. Certain advantages of hybrid methods in comparison to classical model-based measuring methods are demonstrated. Subject of investigation is the determination of the collapsed and the mixture level within pressure vessels under two-phase flow conditions during accidental depressurizations.