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Języki publikacji
Abstrakty
This paper presents an experimental confirmation of the novel method of friction modelling and compensation. The method has been applied to an inverted pendulum control system. The practical procedure of data acquisition and processing has been described. Training of the neural network friction model has been covered. Application of the obtained model has been presented. The main asset of the presented model is its correctness in a wide range of relative velocities. Moreover, the model is relatively easy to build.
Czasopismo
Rocznik
Tom
Strony
875--883
Opis fizyczny
Bibliogr. 6 poz., rys., wykr.
Twórcy
autor
- Division of Dynamics, Lodz University of Technology, ul. Stefanowskiego 1/15, 90-924 Lodz, Poland
Bibliografia
- [1] Marques, F., Flores, P., Claro, J. P., & Lankarani, H.M.: A survey and comparison of several friction force models for dynamic analysis of multibody mechanical systems, Nonlinear Dynamics, 86(3), 2016, 1407-1443.
- [2] Ogata, K.: Modern control engineering, Prentice Hall, 2002.
- [3] Zhongshen, L.: The design of butterworth lowpass filter based on MATLAB [J], Heilongjiang Electronic Technology, 3, 2003, 017.
- [4] Salomon, D.: Curves and Surfaces for Computer Graphics, Springer, 2006.
- [5] Hagan, M. T., & Menhaj, M. B.: Training feed-forward networks with the Marquardt algorithm, IEEE transactions on Neural Networks, 5(6), 1994, 989-993.
- [6] Taylor, J.R.: Classical mechanics, University Science Books, 2005.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-be034dc7-0de8-4850-b8d9-d6c3f0f623c9