Dataset for An Efficient Control-oriented Modeling Approach for Vibration-prone Delta 3D printers using Receptance Coupling

Delta 3D printers have the potential to significantly increase throughput in additive manufacturing because they enable faster and more precise motion when compared to traditional serial-axis 3D printers. Further improvements in motion speed and part quality can be realized through model-based feedforward vibration control, as demonstrated on several serial-axis 3D printers. However, delta 3D printers have not benefited from model-based controllers due to their coupled nonlinear dynamics which vary as a function of position. In this paper, we propose a framework to obtain linear models of delta 3D printers as functions of position. We decompose the dynamics into two sub-models: (1) an experimentally-identified sub-model containing decoupled vibration dynamics; and (2) an analytically-derived sub-model containing coupled rigid-body dynamics. These two sub-models are combined into one using receptance coupling. Employing the proposed approach, experiments are used to demonstrate reasonably accurate predictions of the position-dependent vibration dynamics of a delta 3D printer across its workspace using only two frequency response measurements at one location.