Seguimiento de Trayectorias en Robots Manipuladores: Revisión de Soluciones y Nuevas Propuestas

Abstract

The tracking problem in robot manipulators has been afforded by applying a great variety of controllers, since easy designs based on PD controllers until complex control designs based on adaptive and robust algorithms. These last techniques show some drawbacks, i.e., some bounds in the robot dynamics have to be considered or the controller does not afford with the system constraints. This work makes a revision of the existing classical control techniques for manipulators and proposes a new set of robust and predictive controllers in order to avoid the mentioned problems. Particularly, a self-adaptive robust controller is described which avoids the error produced by an inexact cancellation of the nonlinear dynamics terms. This controller is improved by means of predictive algorithms that include the robot constraints in the control law. This work includes real and simulation results of a PUMA-560 arm of Unimation, which prove the satisfactory performance of the proposed controllers.