Promising Fuzzy Modeling and Control Methodologies for Industrial Applications

Control problems in the industry are dominated by nonlinear and time-varying behavior, many sensors that measure all kinds of variables, many loops and interaction among the control loops. The extraction of (fuzzy) information out of raw data is very important and contains saving potential for industrial applications. Major types of rule-based fuzzy models are described which are based on pre-processed data available within the process. It is shown that these models can be used for different purposes because of their transparency and can be used in industrial applications which are partly described by first principle models and partly by experience built up by designers and operators. Fuzzy control can be based on human experience and can mimic the control actions of human operators. Fuzzy control can also be used in more sophisticated control schemes based on a (fuzzy) models of the process. Applications of fuzzy modeling and control are given.

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