This work presents a repetitive control strategy applied to robotic manipulators. The goal in using this type of controller is the tracking of periodic trajectories in the joint space. The controller is based on the internal model principle with the addition of a repetitive structure and a stabilizing state feedback. The selection of the repetitive controller gains is performed through a convex optimization problem with linear matrix inequalities constraints. The formulation of the optimization problem is based on the Lyapunov stability theory using a Lyapunov-Krasoviskii functional, a quadratic cost for performance adjustment and a restriction to avoid too high controller gains. The performance of the proposed repetitive controller is compared to the performance of the usual computed-torque controller and it is shown that when both controllers are tuned to use the same amount of control energy, the performance of the repetitive controller is better. The implementation uses the the Robot Operating System.