TY  - CONF
AU  - Haber, R.
AU  - Strzelczak, Stanislaw
AU  - Miljković, Zoran
AU  - Castano, F.
AU  - Fumagalli, L.
AU  - Petrović, Milica
PY  - 2020
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3447
AB  - Nowadays, digital twins are fostering the development of plug, simulate and optimize behavior in industrial cyber-physical systems. This paper presents a digital twin-based optimization of a motion system on the basis of a grey wolf optimization (GWO) method. The digital twin of the whole ultraprecision motion system with friction and backlash including a P-PI cascade controller is used as a basement to minimize the maximum position error. The simulation study and the real-time experiments in trajectory control are performed to compare the performance of the proposed GWO algorithm and the industrial method called Fine tune (FT) method. The simulation study shows that the digital twin-based optimization using GWO outperformed FT method with improvement of 66.4% in the reduction of the maximum position error. The real-time experimental results obtained show also the advantage of GWO method with 18% of improvement in the maximum peak error and 16% in accuracy.
PB  - Institute of Electrical and Electronics Engineers Inc.
C3  - Proceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020
T1  - Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems
EP  - 474
SP  - 469
DO  - 10.1109/ICPS48405.2020.9274728
ER  - 

@conference{
author = "Haber, R. and Strzelczak, Stanislaw and Miljković, Zoran and Castano, F. and Fumagalli, L. and Petrović, Milica",
year = "2020",
abstract = "Nowadays, digital twins are fostering the development of plug, simulate and optimize behavior in industrial cyber-physical systems. This paper presents a digital twin-based optimization of a motion system on the basis of a grey wolf optimization (GWO) method. The digital twin of the whole ultraprecision motion system with friction and backlash including a P-PI cascade controller is used as a basement to minimize the maximum position error. The simulation study and the real-time experiments in trajectory control are performed to compare the performance of the proposed GWO algorithm and the industrial method called Fine tune (FT) method. The simulation study shows that the digital twin-based optimization using GWO outperformed FT method with improvement of 66.4% in the reduction of the maximum position error. The real-time experimental results obtained show also the advantage of GWO method with 18% of improvement in the maximum peak error and 16% in accuracy.",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
journal = "Proceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020",
title = "Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems",
pages = "474-469",
doi = "10.1109/ICPS48405.2020.9274728"
}

Haber, R., Strzelczak, S., Miljković, Z., Castano, F., Fumagalli, L.,& Petrović, M.. (2020). Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems. in Proceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020
Institute of Electrical and Electronics Engineers Inc.., 469-474.
https://doi.org/10.1109/ICPS48405.2020.9274728

Haber R, Strzelczak S, Miljković Z, Castano F, Fumagalli L, Petrović M. Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems. in Proceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020. 2020;:469-474.
doi:10.1109/ICPS48405.2020.9274728 .

Haber, R., Strzelczak, Stanislaw, Miljković, Zoran, Castano, F., Fumagalli, L., Petrović, Milica, "Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems" in Proceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020 (2020):469-474,
https://doi.org/10.1109/ICPS48405.2020.9274728 . .