Gain scheduled task space control of multi DOF machine tools with non-linear parallel kinematics

Abstract

Machine tools with multiple degrees of freedom and parallel kinematics offer tremendous opportunities for new kind of processes but at the same time also a lot of control challenges. They are subject to uncertainties in the form of kinematic errors, elasticities and thermal deflections. Their kinematic non-linearity requires the application of model-based control concepts whose full effectiveness can only be unlocked through controls in the task space. In particular, kinematic singularities occur in forming machines such as presses, which make closed-loop control at corresponding operating points considerably more difficult. In this paper, we use the example of a servo-driven press with three ram degrees of freedom to show how parallel kinematic machine tools can be controlled via inverse differential kinematics models in task space and to what extent the controls can benefit from scheduled gain factors. The results are validated both simulatively and experimentally. In the experimental tests, three-dimensional tool paths are traced that can be used to carry out orbital forging processes. Furthermore, the example of a punch hole rolling process demonstrates that the ram pose is controlled more accurately, which also has positive effects on the resulting workpiece geometry. The performance of the developed gain scheduling task space control is compared with that of a robust and non-robust control with static gains.