Tracking of pendulum using particle filter with residual resampling

  • Authors

    • Penumarty Hiranmayi
    • Kola Sai Gowtham
    • S Koteswara Rao
    • V Gopi Tilak
    2018-03-18
    https://doi.org/10.14419/ijet.v7i2.7.10246
  • Bayesian filtering, Extended Kalman Filter, Kalman Filter, Particle filter, Simple pendulum

  • Abstract

    The phenomenon of simple harmonic motion is more vigilantly explained using a simple pendulum. The angular motion of a pendulum is linear in nature. But the analysis of the motion along the horizontal direction is non-linear. To estimate this, several algorithms like the Kalman filter, Extended Kalman Filter etc. are adopted. Here in this paper, Particle filter is chosen which is a method to form Monte Carlo approximations to the solutions of Bayesian filtering equations. Sequential importance resampling based Particle filters are used where the filtering distributions are multi-nodal or consist of discrete state components since under these circumstances the Bayesian approximations do not always work well.

  • References

    1. [1] Simo Sarkka “Bayesian Filtering and Smoothingâ€, Cambridge University Press.

      [2] Torstein A. Myhre, Olav Egeland, “Parameter Estimation for Visual Tracking of a Spherical Pendulum with Particle Filterâ€, 2015 IEEE International Conference on Multisensor Fusion and lntegration for Intelligent Systems (MFI) Sept 14-16, 2015.

      [3] Randal Douc, Olivier Cappe; “Comparison of Resampling Schemes for Particle Filteringâ€, IEEE Xplore, ISPA05.

      [4] Dan Simon, “Optimal State Estimation Kalman, H∞, and Nonlinear Approaches", John Wiley and sons Inc., publishers.

      [5] Simo Sarkka, “Bayesian Estimation of Time-Varying Systems, Copyright (C) Simo Särkkä, 2009–2012.

      [6] Doucet, A., De Freitas, N., and Gordon, N. 2001. Sequential Monte Carlo Methods in Practice. Springer

      [7] Hong, Shaohua, Jianxing Jiang, and Lin Wang. "Improved residual resampling algorithm and hardware implementation for particle filters", 2012 International Conference on Wireless Communications and Signal Processing (WCSP), 2012.

      [8] Li, Tiancheng, MiodragBolic, and Petar M. Djuric. "Resampling Methods for Particle Filtering: Classification, implementation, and strategies", IEEE Signal Processing Magazine, 2015.

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  • How to Cite

    Hiranmayi, P., Sai Gowtham, K., Koteswara Rao, S., & Gopi Tilak, V. (2018). Tracking of pendulum using particle filter with residual resampling. International Journal of Engineering & Technology, 7(2.7), 12-15. https://doi.org/10.14419/ijet.v7i2.7.10246

    Received date: 2018-03-18

    Accepted date: 2018-03-18

    Published date: 2018-03-18