@inproceedings{MuellerEndisch2016, author = {M{\"u}ller, Tino and Endisch, Christian}, title = {Compensation techniques for iterative rig control in multi-axial durability testing}, booktitle = {2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5090-1314-2}, doi = {https://doi.org/10.1109/ETFA.2016.7733517}, year = {2016}, language = {en} } @inproceedings{MuellerEndisch2017, author = {M{\"u}ller, Tino and Endisch, Christian}, title = {An estimation based iterative learning control approach for cross-coupled vehicle test systems}, booktitle = {2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5090-6000-9}, issn = {2159-6255}, doi = {https://doi.org/10.1109/AIM.2017.8014210}, pages = {1375 -- 1381}, year = {2017}, language = {en} } @inproceedings{MuellerVoegeleEndisch2016, author = {M{\"u}ller, Tino and V{\"o}gele, Ulrich and Endisch, Christian}, title = {Disturbance compensation for iterative control of suspension durability test rigs}, booktitle = {2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5090-2065-2}, doi = {https://doi.org/10.1109/AIM.2016.7577011}, pages = {1675 -- 1681}, year = {2016}, language = {en} } @article{MuellerZiegmannKrueneretal.2016, author = {M{\"u}ller, Tino and Ziegmann, Johannes and Kr{\"u}ner, Simon and Endisch, Christian}, title = {Optimization of inverse model identification for multi-axial test rig control}, volume = {2016}, pages = {01002}, journal = {MATEC Web of Conferences}, number = {42}, publisher = {EDP Sciences}, address = {Les Ulis}, issn = {2261-236X}, doi = {https://doi.org/10.1051/matecconf/20164201002}, year = {2016}, abstract = {Laboratory testing of multi-axial fatigue situations improves repeatability and allows a time condensing of tests which can be carried out until component failure, compared to field testing. To achieve realistic and convincing durability results, precise load data reconstruction is necessary. Cross-talk and a high number of degrees of freedom negatively affect the control accuracy. Therefore a multiple input/multiple output (MIMO) model of the system, capturing all inherent cross-couplings is identified. In a first step the model order is estimated based on the physical fundamentals of a one channel hydraulic-servo system. Subsequently, the structure of the MIMO model is optimized using correlation of the outputs, to increase control stability and reduce complexity of the parameter optimization. The identification process is successfully applied to the iterative control of a multi-axial suspension rig. The results show accurate control, with increased stability compared to control without structure optimization.}, language = {en} }