In our work we present a Fuzzy variant of the Multiverse Optimizer Algorithm (MVO), this variant uses Type-2 Fuzzy Logic and is called Fuzzy Multiverse Optimizer Algorithm Interval Type-2 (FMVOit2); we use an interval Type-2 fuzzy inference system, improving previous works that used Type-1 fuzzy inference systems and the use of chaos theory. This variant has been used for benchmark mathematical functions and showed some significant improvement over the original MVO. For this reason, we are comparing multiple variants of the algorithm of other works on fuzzy controller optimization. The case of study presented is the temperature control in a shower, which has two outputs to adjust: the flow of water and the temperature that has to obtain the water. The aim of this paper is to introduce a novel FMVOit2 variant of the algorithm for optimizing fuzzy controllers by adjusting the parameters of the membership functions. This variant is evaluated in comparison with other algorithmic versions and subsequently applied to various case studies.