Application of Infinite Memory Structure and Finite Memory Structure Filters for Electric Motor System

  • Authors

    • Pyung Soo Kim
    • Seok Jun Kwon
    https://doi.org/10.14419/ijet.v7i4.38.29220
  • Electric motor system, Finite memory structure, Infinite memory structure, Nominal system, State estimation filter, Temporary uncertain system.

  • Abstract

    In this paper, both IMS and FMS filters are applied for the estimation filtering of electric motor systems. Firstly, the electric motor system and its state-space model is described, Secondly, IMS and FMS filters are briefly introduced and compared. These two filters are represented by the summation form and use the rotational speed as the output measurement unlike the existing work. Thirdly, comprehensive simulation works are performed for both certain system and temporarily uncertain system. Simulations results show that the FMS filter can be better than the IMS filter for the temporarily uncertain system. It is also shown that there can be the trade-off between two filtering performance indices, estimation error and tracking speed in terms of the memory length.

     

     

  • References

    1. [1] A. Hughes and B. Drury, Electric Motors and Drives: Fundamentals, Types and Applications, 4th Edition, Elsevier, 2013

      [2] B. Messner, D. Tilbury, R. Hill, and J. D. Taylor, Suspension: State-Space Controller Design: Control Tutorials for MATLAB and Simulink (CTMS). University of Michigan, 2017.

      [3] D. Pal, “Modeling, analysis and design of a DC motor based on state space approachâ€, International Journal of Engineering Research & Technology, vol. 5, no. 2, pp. 293~296, 2016.

      [4] T. Abut, “Modeling and optimal control for a DC motorâ€, International Journal of Engineering Trends and Technology, vol. 32, no. 3, pp. 146~150, 2016.

      [5] Z. Q. Zheng, Y. H. Zhang, J. S. Zhang, “Application of Kalman filter in DC motor speed control systemâ€, Applied Mechanics and Materials. vol. 150, pp. 129-132, 2012.

      [6] M. S. Grewal, “Applications of Kalman filtering in aerospace 1960 to the presentâ€, IEEE Control Systems, vol. 30, no. 3, pp. 69–78, 2010.

      [7] F. Auger, M. Hilairet, J.M. Guerrero, E. Monmasson, T. Orlowska-Kowalska, S. Katsura, “Industrial Applications of the Kalman Filter: A Reviewâ€, IEEE Transactions on Industrial Electronics, vol. 60, no. 12, pp. 5458-5471, 2013.

      [8] P. S. Kim, “An alternative FIR filter for state estimation in discrete-time systems,†Digital Signal Processing, vol. 20, no. 3, pp. 935~943, 2010.

      [9] S. Zhao, Y. S. Shmaliy, B. Huang, and F. Liu, “Minimum variance unbiased FIR filter for discrete time-variant systems,†Automatica, vol. 53, no. 2, pp. 355~361, 2015.

      [10] P. S. Kim, “A finite memory structure smoother with recursive form using forgetting factor,†Mathematical Problems in Engineering, vol. 2017, pp. 1~6, 2017.

      [11] Y. S. Shmaliy, S. Zhao, and C. K. Ahn, “Unbiased finite impulse response filtering: An iterative alternative to Kalman filtering ignoring noise and initial Conditions,†IEEE Control Systems, vol. 37, no. 5, pp. 70–89, 2017.

      [12] J. M. Pak, P. S. Kim, S. H. You, S. S. Lee, and M. K. Song, “Extended least square unbiased FIR filter for target tracking using the constant velocity motion model,†International Journal of Control, Automation and Systems, vol. 15, no. 2, pp. 947~951, 2017.

      [13] Y. S Shmaliy, S. H Khan, S. Zhao, O. Ibarra-Manzano, “General unbiased FIR filter with applications to GPS-based steering of oscillator frequency,†IEEE Transactions on Control Systems Technology, vol. 25, no. 3, pp. 1141-1148, 2017.

      [14] P. S. Kim, M. S. Jang, S. Y. Kang, and E. H. Lee, “A finite memory structure filtering for indoor positioning in wireless sensor networks with measurement delay,†International Journal of Distributed Sensor Networks, vol. 13, no. 1, pp. 1~8, 2017.

      [15] S. J, Kwon, P. S. Kim, “A finite memory structure filtering for DC motor system with temporary uncertainties,†Journal of Institute of Control, Robotics and Systems(Korean), vol. 24, no. 6, pp. 573~579, 2018.

  • Downloads

  • How to Cite

    Soo Kim, P., & Jun Kwon, S. (2018). Application of Infinite Memory Structure and Finite Memory Structure Filters for Electric Motor System. International Journal of Engineering & Technology, 7(4.38), 1630-1634. https://doi.org/10.14419/ijet.v7i4.38.29220

    Received date: 2019-05-13

    Accepted date: 2019-05-13