Sintonización genética de sistema de inferencia difuso aplicado al control de posición en un motor de corriente directa

This paper proposes the development and application of a genetic algorithm to improve the function of a fuzzy inference machine used in the shaft position control of a direct current motor. In this first stage, the study is executed on system leaving out the transfer function that defines the dynamic characteristics of the mentioned actuator, which leads to the subsequent physical verification of its behavior. The analysis of the calculated error is considered as the difference between the desired position and the current position reached by motor shaft, as well as the signal that the inference system will generate to correct the given magnitude of error. Likewise, the theoretical foundations that support this application and the methodology executed to obtain the results that confirm the effectiveness in the use of the genetic algorithm as a means of tuning the fuzzy inference system developed are described, when describing a global error lower than 20% in the control action deducted with respect to the one desired.