Experimental dataset for model identification and validation of feedforward control on a five-axis milling machine.

This dataset belongs to the Open Access publication "Increasing dynamic accuracy of machine tools using predictive feedforward optimization with hybrid modeling" (doi: 10.1016/j.rcim.2025.103137) A detailed description of the setup can be found in the publication.

Feedback controllers from frequency inverter:

PI velocity controller with Kp = 0.035 [Nm/(rad/s)], Tn = 2.6 [ms]. P position controller with Kp = 35 [1/s].

The dataset contains the following folders (Feel free to contact the dataset owner if you have any questions about the dataset.):

Identification measurements for identification of discrepancy model with different constant velocities as reference, and velocity sweeps for identification in frequency domain.

Validation\energy_consumption measured energy consumption on the test bench of different feedforward schemes, quantified by direct current (DC) power

Validation\multi-axis butterfly contour multi-axis tracking experiments comparing different feedforward schemes, the used butterfly G-code is also provided

Validation\sensitivity analysis sensitivity analysis of the proposed MPFFC scheme against parametric model uncertainty

Validation\tracking single axis (const velocity) single-axis tracking experiments at (unseen) consant velocities

Validation\tracking single axis (transient) single-axis tracking experiments demonstrating transient behavior

TwinCAT 3, 4024.65

ctrlX DRIVE, 1.16.2