A new approach of GA-based type reduction of interval type-2 fuzzy model for nonlinear MIMO system: Application in methane oxidation process

Abstract

The aim of this paper is the application of a type-2 fuzzy model to a nonlinear MIMO system. In the suggested approach, genetic algorithm is employed to find the optimal type reduction of the interval type-2 fuzzy model for model prediction. To verify its performance, the proposed method is used in prediction of the methane conversion and the formic acid selectivity of the methane oxidation process with H2O2. In this process, the input variables are temperature, pressure, time on stream, catalyst content, H2O2 concentration and stirring speed. Interval type-2 fuzzy logic model has designed with reduced rules number compared with the type-1 fuzzy model. The results confirm that the proposed method based on type reduction interval type-2 fuzzy model outperforms the other strategies with an R2 value of greater than 0.988.