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Design of a Neural Network for an Identification of a Robot Model with a Positive Definite Inertia Matrix

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Artifical Intelligence and Soft Computing (ICAISC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6114))

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Abstract

This article presents a method of designing the neural network for the identification of the robot model in a form of Lagrange-Euler equations. It allows to identify the positive definite inertia matrix. A proposed design of a neural network structure is based on the Cholesky decomposition.

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References

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Author information

Authors and Affiliations

  1. Institute of Automatic Control and Robotics, Warsaw University of Technology, 02-525, Warszawa, s̀w.Andrzeja Boboli 8, Poland

    Jakub Możaryn & Jerzy E. Kurek

Authors
  1. Jakub Możaryn
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  2. Jerzy E. Kurek
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Academy of Humanities and Economics in Łódź, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley Initiative in Soft Computing (BISC), 94720-1776, CA

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Louisville, 40292, Louisville, KY

    Jacek M. Zurada

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Możaryn, J., Kurek, J.E. (2010). Design of a Neural Network for an Identification of a Robot Model with a Positive Definite Inertia Matrix. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artifical Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13232-2_39

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  • DOI: https://doi.org/10.1007/978-3-642-13232-2_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13231-5

  • Online ISBN: 978-3-642-13232-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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