Replication Data for: Model Predictive Position Control for Electrically Preloaded Rack-and-Pinion Drives

DOI

This dataset contains all experimental results presented in the paper "Model Predictive Position Control for Electrically Preloaded Rack-and-Pinion Drives".

The paper presents a cascaded model predictive control approach to increase the accuracy and dynamics of an electrically preloaded rack-and-pinion drive. Three different internal models for the model predictive controller, each with a different model order, are investigated and compared. The proposed control approach is validated in real-time on a test bench, and experimental results show improved position control in comparison to a standard proportional controller with feedforward control.

This dataset is structured accoring to the figures with experimental results in the paper:

  data_Fig4: Data for the frequency response of the closed loop velocity controlled plant with the approximated models.
  data_Fig5: Data for the frequency response of the closed loop transfer function for the controllers compared.
  data_Fig6: Data for the comparison of the cascaded controllers.
  data_Fig7: Data for the comparison of the disturbance rejection behavior.
Identifier
DOI https://doi.org/10.18419/DARUS-5687
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-5687
Provenance
Creator Leipe, Valentin ORCID logo
Publisher DaRUS
Contributor Leipe, Valentin; ISW DaRUS Admin
Publication Year 2026
Funding Reference DFG 556052806
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Leipe, Valentin (University of Stuttgart); ISW DaRUS Admin (University of Stuttgart)
Representation
Resource Type Dataset
Format application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
Size 105636; 38956; 1187046; 70135
Version 1.0
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences; Mechanical and industrial Engineering