Description: Interval type-2 fuzzy models in identification problems of multiple-input multiple output objects are considered. The mathematical model that can be the base of fuzzy logic adviser is proposed. This model helps to increase identification and diagnostic quality of complex multiple-input multiple output objects in technical systems. The genetic algorithm of multiple-input multiple output interval type-2 fuzzy model is proposed. This algorithm uses four crossover schemes (single point, multiple point, intermediate, arithmetic) and two mutation schemes (uniform and gaussian).
Keywords: interval type-2 fuzzy model, multiple-input multiple output object, fuzzy logic adviser, genetic algorithm