Optimization of Membership Function Parameters for Fuzzy Controllers in Cruise Control Problem Using the Multi-verse Optimizer

In this paper we propose the application of metaheuristics to optimize control systems that use fuzzy logic, involving the multi-verse optimizer in various situations that involve control. The systems that we study are benchmark fuzzy controllers, like the case of cruise control, which focuses on controlling the velocity that a vehicle has to achieve and maintain in an optimal environment for its implementation, without constraints of the outside world like air friction or the use of inclination. This is by using a simple one input-output fuzzy system that is being optimized in its membership functions parameters; also another system used to prove the functionality of the algorithm is a case of approximation for the tipper system, were the objective is to approximate the system using a two input-one output fuzzy system. The main goal is to introduce the multi-verse optimizer in control problems as a great choice for these systems.