Focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area Demonstrates that using fuzzy systems combined with the differential evolution algorithm produces better results in each of the controllers and with increasing uncertainty, the results are even better Proposes methods using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers’ behavior in complex control problems Explains the proposed method which is tested using five benchmark control problems: the water tank, temperature, mobile robot, inverted pendulum controllers, and the D.C. motor

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