Self Tuning Fuzzy controller of nonlinear systems

The present paper is dedicated for the presentation and implementation of an optimized technique allowing an online adjustment of the fuzzy controller parameters. Indeed, we have obtained an on-line optimized zero order Takagi-Sugeno type FIS. This method is simple and safe since, it leads to very quick and efficient optimization technique. A comparison between the STFIS (Self Tuning Fuzzy Inference System) and PID controller's gives the improvement of the ability in sense of adaptation among the presence of noise of neuro-fuzzy controller.