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The simulation results provide evidence that the fuzzy marine predator’s algorithm exceeds the results of the marine predator’s algorithm are compare, in the design and optimization of the Interval Type-2 Fuzzy Logic controller. The fuzzy marine predators algorithm is used to search for the best distribution of the values of the parameters of the membership functions of a fuzzy controller for the plant of an autonomous mobile robot, bearing in mind different degrees of noise to analyze the performance when simulating the Interval Type-2 Fuzzy Logic controller. the fuzzy marine predator algorithm evaluates its performance with a group of 19 benchmark functions of the CEC-2017 that is composed of 2 unimodal functions, 7 multimodal functions, and 10 hybrid functions, the results show that the fuzzy marine predators algorithm provides better results than MPA. Its novelty is presented in the application of Type-1 and Interval Type-2 Fuzzy Logic systems, which balance the degree of exploration and exploitation through its iterations and through the search for the optimum of its parameters FADS and P, the second novelty is given as the fuzzy variation Interval Type-2 of a CF parameter, which varies the advance of the predator, memorized separately by the best fitness achieved by iteration, and in this way to coordinate the actions of exploration and exploitation.
This is presented as an improved variant of the marine predators algorithm and its utility in control applications.
This paper presents the fuzzy variant of a recent naturally-based metaheuristic that follows the rules of the best feeding strategies with the predator and prey rate regime of marine ecosystems, called the fuzzy marine predators algorithm (FMPA).
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