Data for: Online motion accuracy compensation of industrial servomechanisms using machine learning approaches

Here are shared the files related to the study presented in the paper: Title: "Online motion accuracy compensation of industrial servomechanisms using machine learning approaches" Authors: Pietro Bilancia, Alberto Locatelli, Alessio Tutarini, Mirko Mucciarini, Manuel Iori and Marcello Pellicciari Two folders are shared: 1) Experimental Data --> contains the results obtained from an extensive experimental campaign carried out on a test rig for industrial servomechanisms. - Speed --> {100,200,...,18000] rpm (18 levels) - Output torque --> {0,100,...,1800} Nm (19 levels) - Oil temperature --> {25,30,35}°C (3 levels) 2) Machine learning models --> ONNX files saved from Python after training and readily available to be imported and utilized within Programmable Logic Controllers to achieve motion prediction and compensation.