Estimation of Continuous-Time Nonlinear Systems by Using the Unscented Kalman Filter

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Author(s)

    • ZHENG Min
    • Graduate School of Advanced Technology and Science, The University of Tokushima
    • IKEDA Kenji
    • Institute of Technology and Science, The University of Tokushima

Abstract

This paper proposes a continuous-time model estimation method by using the Unscented Kalman Filter (UKF) from sampled I/O data, in which plant parameters as well as the initial state are estimated. The initial state is estimated based on a backward system of the plant, and the parameters are estimated by using an iterated UKF, which repeats the estimation of the forward system and the backward system alternately. In order to demonstrate the effectiveness of the proposed method, a rotary pendulum is considered to estimate the parameters of a continuous-time nonlinear system.

Journal

  • SICE Journal of Control, Measurement, and System Integration

    SICE Journal of Control, Measurement, and System Integration 3(5), 324-329, 2010

    The Society of Instrument and Control Engineers

Codes

  • NII Article ID (NAID)
    130004552799
  • Text Lang
    ENG
  • ISSN
    1882-4889
  • Data Source
    J-STAGE 
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