Using genetic algorithms in fine-tuning of fuzzy logic controller

This paper presents a novel and robust GA-fuzzy controller structure. This controller incorporates genetic algorithms and fuzzy logic in order to control the complicated nonlinear plant. The GA is used to optimize the parameters of fuzzy logic and its control rules. The results of simulation studies for an industrial plant and inverted pendulum demonstrate that the controller is robust and efficient.

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