Genetic algorithm optimization of a model-free fuzzy control system

In this work, we present an approach, based on a genetic algorithm optimization search, for determining the values of the parameters of an adaptive stable fuzzy control system suitable to drive a given plant to a desired reference trajectory. The method is demonstrated on a naturally unstable system taken from the literature and then applied to the well known Chernick's model of a nuclear reactor.