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Conference on Automation

AUTOMATION 2018: Automation 2018 pp 132–141Cite as

Real-Time and Low Phase Shift Noisy Signal Differential Estimation Dedicated to Teleoperation Systems

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

Abstract

The paper contains a description of a real-time differentiation algorithm dedicated to teleoperation systems. The algorithm is based on the least squares polynomial approximation method and it is a modified version of a local and nearest neighbors samples based approach. The algorithm fits a defined polynomial to an asymmetric data set. In this case, the nearest neighbor samples are only taken from the one side of the filtered vector of a signal samples. This feature allowed to reduce the value of the phase shift, especially for a low frequency spectrum, where man-machine control interfaces are usually operating. The strong reduction of a phase shift allowed to minimize the variable time delay of the estimated signal differential according to a measured control signal.

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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

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  1. Mateusz Saków
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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. (2018). Real-Time and Low Phase Shift Noisy Signal Differential Estimation Dedicated to Teleoperation Systems. 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_12

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  • DOI: https://doi.org/10.1007/978-3-319-77179-3_12

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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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