In a practical, certain physical characteristics of the Asynchronous Machine (MAS) can vary during operation, which brings parametric variations to the system model. In addition, for most systems, the mathematical model is not known exactly because of the non-linearity of the actual process. The usual procedure is to design the controller based on a simplified model and with nominal physical parameters. This simplification also causes additional uncertainties on the model parameters and the conventional PI controller no longer allows the required adjustment qualities. The problem can be solved by adaptive control whereby the controller is forced to adapt to a wide variety of operating conditions; by exploiting the information provided by the system in real time. In this paper, we will proceed to a hybridization technique between the PI setting and the fuzzy logic; in fact, the parameters of the PI controller will be adapted by a fuzzy inference, as will be detailed later. We will get a controller called Fuzzy PI (PI-FLC).