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Interval Type-3 Fuzzy Differential Evolution with Crossover Parameter Adaptation Applied to Fuzzy Control of DC Motor Speed
Patricia Ochoa, Cinthia Peraza, Oscar Castillo and Patricia Melin
The study and application of fuzzy logic have advanced significantly to provide solutions to increasingly more complex problems. The main advantage of fuzzy logic is the utilization of linguistic variables and the creation of rules based on the behavior of the problem to be modeled. Finding the best solution to a highly complex control problem is a constant challenge. Fuzzy logic allows us to manage uncertainty, thereby obtaining precise and highly efficient results. The objective of this work is to employ interval type-3 fuzzy logic to adjust the Crossover (CR) of differential evolution and apply the method (DE+IT3FS) to the optimization of a controller for a problem. The results from the simulation, both without noise and with noise applied to the controller, are presented, highlighting the effectiveness of the method when compared to existing methods.
Keywords: Type-3 Fuzzy logic, differential evolution, parameter adaptation