The paper presents some novel research on applications of Type-2 Fuzzy Logic Systems to support the Selective Catalytic Reduction process (SCR). The aim of the research is to design and test higher order fuzzy logic systems and their genuine modifications to manage data in DeNOx systems responsible for controlling emission of nitrogen oxides (NO, NO2). Since in real applications, it is still performed under the supervision of a human expert, the scope is to replace, at least partially, his/her participation with dedicated type-2 fuzzy logic systems. As the result, it is shown that the proposed systems with new means of learning fuzzy IF-THEN rules allow us to compute parameters much closer to those determined by experts, even in a comparison to some earlier approaches based on traditional fuzzy logic.
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