Design of an adaptive fuzzy logic controller

This paper proposes an adaptive fuzzy logic controller based on the structure of the self-tuning regulator and neural network and genetic algorithm techniques. The system has two main functions: online process identification and fuzzy logic controller modification using the identified model. A recurrent neural network performs the identification and a genetic algorithm obtains the best process model and evolves the best controller design. The paper presents simulation results to show the effectiveness of the proposed system.<<ETX>>