An adaptive model-free fuzzy controller

In this paper, we present an adaptive, stable fuzzy controller whose parameters are optimized via a genetic algorithm. The controller model is capable of building itself on the basis of measured plant data and then of adapting to new dynamics. The stability of the overall system, made up of the plant and the controller, is guaranteed by Lyapunov's theory. As a case study, the stable adaptive fuzzy controller is employed to drive the narrow water level of a simulated Steam Generator (SG) to a desired reference trajectory. The numerical results confirm that the controller bears good performances in terms of small oscillations and fast settling time even in presence of external disturbances. (authors)