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In this work, the problem of trajectory identification of nonlinear systems using neural networks is presented. The theoretical results are verified by means of an experimental study in which the nonlinear system is made up of a permanent magnet DC servomotor with reduction that also has a rod coupled to the motor shaft, in the manner of a One Degree of Freedom Robotic Arm ( BRIL), where the rod is capable of moving in a plane perpendicular to the motor axis and is controlled by the armature voltage applied to the servomotor.