This dataset includes results of simulation and experiment for tuning of bumpless feedforward controller. The tuninig of FF and the simultaneous tuning of FF and DOB are selected as comparsion group. Their results are also included in this dataset. For each method, two parameters are chosen to be tuned in their inverse uniform model or inverse sub-model. The results of each iteration for every method and every trajectory are also included. In simuation file, there are five group of result. For each group, results of three methods are included.
This data is mainly used for the calibration of the long-stroke Cartesian robot. The position data is measured by Leica Laser Tracker, including the data of the identification of kinematics parameters, the data of the Gaussian process regression model validation and prediction, and the data that the compensation results based on HTM, HTM+SBD, HTM+GPR, HTM+SBD+GPR model in different position points.
The data are used to identify the kinematic parameters deviation of Cartesian robot, train Gaussian Process Regression (GPR) model, record the compensation result of four calibration methods under different loading conditions.