Backlash Identification in Industrial Positioning Systems Aided by a Mobile Accelerometer Board with Wi-Fi

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Tantau, M.; Perner, L.; Wielitzka, M.: Backlash Identification in Industrial Positioning Systems Aided by a Mobile Accelerometer Board with Wi-Fi. In: Gusikhin, O.; Madani, K.; Zaytoon, J. (Eds.): Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics. Prague : SciTePress, 2020, S. 576-584. DOI: https://doi.org/10.5220/0009805305760584

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/11505

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Sum total of downloads: 174




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Abstract: 
In electromechanical motion systems performance measures such as positioning accuracy, dynamic stiffness and control bandwidth are severely limited by backlash. Several control schemes based on backlash compensation or switching control of hybrid systems are known, but many of these approaches require the exact backlash width as an input parameter. Several existing approaches for backlash identification are limited in accuracy because the load-side velocity is required but it is not directly measurable. In this paper a method for backlash identification tailored to electromechanical motion systems with rotary motor and translationally moving load is proposed. A mobile sensor board with inertial measurement unit (IMU) is mounted temporarily on the load and serves to acquire the accelerations during the experiment. The connection to the host-PC is wireless, time synchronisation is not required. It is shown in experiments on a testbed with an adjustable backlash coupling but otherwise i ndustry-like equipment that high accuracies can be achieved.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: BookPart
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 53 30.46%
2 image of flag of United States United States 31 17.82%
3 image of flag of Czech Republic Czech Republic 25 14.37%
4 image of flag of Russian Federation Russian Federation 23 13.22%
5 image of flag of China China 8 4.60%
6 image of flag of Taiwan Taiwan 4 2.30%
7 image of flag of Italy Italy 3 1.72%
8 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 3 1.72%
9 image of flag of Israel Israel 3 1.72%
10 image of flag of Australia Australia 3 1.72%
    other countries 18 10.34%

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