Adaptive Force Control for Robotic Disk Grinding

Abstract

In this paper, the design and implementation of an adaptive predictive force controller for robotic grinding are described. The force regulation is established by modifying, on-line, the robot's programmed position control commands. The experiments were conducted using an industrial robot equipped with a pneumatic grinder and a six degrees of freedom force sensor. Two predictive control laws, namely; Generalized Predictive Control (GPC), and Extended Horizon Control (EHC) are evaluated by simulation and experimentally. The control laws are designed based on accurate model(s) for the open-loop dynamic of the robot and grinding process, which are identified from experimental data. The results show that both controllers are able to effectively regulate the normal grinding force and compensate for force errors caused by step force disturbances and robot path tracking errors. A slightly better control performance was achieved, however, using the Generalized Predictive Controller.