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Transport Delay and First Order Inertia Time Signal Prediction Dedicated to Teleoperation

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Automation 2018 (AUTOMATION 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 743))

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Abstract

In the paper a sensor-less control scheme for a bilateral teleoperation system with a force-feedback based on a prediction of an input of a non-linear inverse model by prediction blocks is presented. The prediction method was designed to minimize the effect of the transport delay and the phase shift of sensors, actuators and mechanical objects. The solution is an alternative to complex non-linear models like artificial neural networks, which requires complex stability analysis and control systems with high computing power. Also, in this paper we had compared a transport delay and first order inertia continues approach. The effectiveness of both approaches has been verified on the hydraulic manipulator test stand.

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Acknowledgments

The work was carried out as part of the PBS3/A6/28/2015 project, “The use of augmented reality, interactive voice systems and operator interface to control a crane”, financed by NCBiR.

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Authors and Affiliations

  1. Faculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology, 19 Piastów Avenue, 70-310, Szczecin, Poland

    Mateusz Saków & Karol Miądlicki

Authors
  1. Mateusz Saków
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  2. Karol Miądlicki
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Corresponding author

Correspondence to Mateusz Saków .

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Editors and Affiliations

  1. Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Roman Szewczyk

  2. Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Cezary Zieliński

  3. Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Małgorzata Kaliczyńska

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Saków, M., Miądlicki, K. (2018). Transport Delay and First Order Inertia Time Signal Prediction Dedicated to Teleoperation. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2018. AUTOMATION 2018. Advances in Intelligent Systems and Computing, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-319-77179-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-77179-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77178-6

  • Online ISBN: 978-3-319-77179-3

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