Uninorm-based models for FLC systems

Uninorms continue to bring new possibilities in fuzzy systems models. In the paper it is presented how uninorm-based approximate reasoning can be applied, based on similarity measures of fuzzy sets and residuum of uninorms. The investigations are focused on distance based operators, and its represents in the group of uninorms. Considering that the uninorms are parameter-dependent norms, we can influence the behavior of the system by changing or sliding the parameter values and by this the construction of the uninorm, which is built-in in the inference mechanism. Along with the uninorm parameters, the structure of the fuzzy sets can also be modified in order to improve the behavior of the entire fuzzy-controlled system.