In this paper, four control strategies are developed and evaluated for the trajectory-tracking of a two-degree-of-freedom SCARA-type robotic manipulator: (i) a proportional-derivative controller (PD), (ii) a proportional-derivative controller with friction compensation (PD + G), (iii) an inverse-dynamics controller and (iv) a sliding-mode controller with a dynamic model (SMCD). These controllers are implemented in a dynamic model of a manipulator robot, and their performance is assessed based on trajectory-tracking accuracy and robustness against disturbances. Robustness tests are conducted by varying the parameters of the dynamic model of the robot. The performance of each controller is analyzed using the Integral Squared Error (ISE) and the Integral of Time-weighted Squared Error (ITSE) indexes to compare their effectiveness. This study offers a comprehensive evaluation of each control strategy, demonstrating that the SMCD achieves the optimal balance between accuracy and disturbance robustness.

This article addresses the need to modernize industrial safety training in production plants, as traditional methods have proven to be ineffective and tedious. An immersive virtual environment was developed using Unreal Engine 5, based on 3D reconstructions, allowing users to interact with simulated hazards in a virtualized industrial space. The system was validated through surveys conducted with operational personnel, obtaining 100% acceptance and recommendation for implementation. The results show a high perception of realism and usefulness, positioning the environment as a viable alternative to traditional safety training methodologies.