Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems

Haber Guerra, Rodolfo E. and Strzelczak, Stanisław and Miljković, Zoran and Castaño Romero, Fernando and Fumagalli, luca and Petrović, Milica (2020). Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems. In: "3rd. IEEE Conference on Industrial Cyber-Physical Systems", June 10-12, 2020, Tampere, Finland.

Description

Title: Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems
Author/s:
  • Haber Guerra, Rodolfo E.
  • Strzelczak, Stanisław
  • Miljković, Zoran
  • Castaño Romero, Fernando
  • Fumagalli, luca
  • Petrović, Milica
Item Type: Presentation at Congress or Conference (Article)
Event Title: 3rd. IEEE Conference on Industrial Cyber-Physical Systems
Event Dates: June 10-12, 2020
Event Location: Tampere, Finland
Title of Book: Proceedings of 3rd. IEEE Conference on Industrial Cyber-Physical Systems
Date: 12 June 2020
Subjects:
Freetext Keywords: digital twin, optimization, grey wolf optimizer, controller tuning, CNC machine tools
Faculty: Centro de Automática y Robótica (CAR) UPM-CSIC
Department: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
Creative Commons Licenses: Recognition - Non commercial

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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.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainDPI2017-86915-C3-3-RCOGDRIVEUnspecifiedTécnicas de Inteligencia Artificial y Ayuda a la Navegación Autónoma

More information

Item ID: 64939
DC Identifier: http://oa.upm.es/64939/
OAI Identifier: oai:oa.upm.es:64939
Deposited by: Dr. Rodolfo Haber
Deposited on: 23 Oct 2020 09:32
Last Modified: 23 Oct 2020 09:32
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