Abstract

Industrial growth over time has demanded the use of robots to perform complex tasks in processes. One way to address this challenge has been through high-performance controllers. In this study, a 3-Degrees-of-Freedom (DoF) manipulator robot was modeled and simulations were performed to control its trajectory using artificial intelligence-based controllers: fuzzy PD+I and neural networks. Additionally, a conventional PID was used, and finally, the three controllers were evaluated with two types of trajectories. The results showed the fuzzy PD+I to be the most effective controller regardless of the presence of abrupt changes in direction.