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Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems
dc.creator | Haber, R. | |
dc.creator | Strzelczak, Stanislaw | |
dc.creator | Miljković, Zoran | |
dc.creator | Castano, F. | |
dc.creator | Fumagalli, L. | |
dc.creator | Petrović, Milica | |
dc.date.accessioned | 2022-09-19T19:09:58Z | |
dc.date.available | 2022-09-19T19:09:58Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | https://machinery.mas.bg.ac.rs/handle/123456789/3447 | |
dc.description.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. | en |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
dc.relation | H2020 project Grant 826417 Power2Power | |
dc.relation | NAWA Polish agency through the IPAE project: “Industry 4.0 in Production and Aeronautical Engineering” | |
dc.relation | DPI2017 - Performance indices in experimental results 86915-C3-1-R "Cognitive inspiration navigation for autonomous driving" | |
dc.rights | openAccess | |
dc.source | Proceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020 | |
dc.subject | optimization | en |
dc.subject | grey wolf optimizer | en |
dc.subject | digital twin | en |
dc.subject | controller tuning | en |
dc.subject | CNC machine tools | en |
dc.title | Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems | en |
dc.type | conferenceObject | |
dc.rights.license | ARR | |
dc.citation.epage | 474 | |
dc.citation.other | : 469-474 | |
dc.citation.rank | M33 | |
dc.citation.spage | 469 | |
dc.identifier.doi | 10.1109/ICPS48405.2020.9274728 | |
dc.identifier.fulltext | http://machinery.mas.bg.ac.rs/bitstream/id/2045/3444.pdf | |
dc.identifier.scopus | 2-s2.0-85098700919 | |
dc.type.version | publishedVersion |