Hierarchical Predictive Control within an Open Architecture Virtual Machine Tool

The proposed hierarchical structure, based on the a priori knowledge of the toolpath and using the receding horizon principle, aims at reducing the degradation of tracking performances due to control signals saturation. Starting with the predictive feed drives control as first level, a second one, called trajectory supervisor, modifies in a predictive way as well the axial setpoints in order to minimize the impact of control signals saturation on the tracking accuracy. The third level, called trajectory regenerator, acts with an anticipative effect when the modified setpoints are too distant from the original ones and recomputes the entire toolpath. This strategy is further tested within an open architecture virtual machine tool.