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Robust Filtering for Discrete Systems with Unknown Inputs and Jump Parameters

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Abstract

The paper deals with robust filtering algorithms for discrete systems with unknown inputs (disturbances) and Markovian jump parameter. The proposed filtering algorithm is based on the separation principle, minimization of a quadratic criterion and the use of Kalman filters with unknown input and smoothing procedures. Solving a non-stationary problem is represented solving a two-point boundary value problem in kind of difference matrix equations. In the stationary case problem is represented matrix algebraic equations. Robustness ensures the stability of the filter dynamics when errors occur in identifying the jump parameter. An example is provided to illustrate the proposed approach, which showed that the use of smoothing procedures for estimating an unknown input improves the accuracy of estimates.

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Funding

This work was supported by the RFBR according to the research project no. 19-31-90080.

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Authors and Affiliations

  1. Department of Applied Mathematics, Institute of Applied Mathematics and Computer Science National Research Tomsk State University, 634050, Tomsk, Russia

    K. S. Kim & V. I. Smagin

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  1. K. S. Kim
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  2. V. I. Smagin
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Correspondence to K. S. Kim or V. I. Smagin.

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Kim, K.S., Smagin, V.I. Robust Filtering for Discrete Systems with Unknown Inputs and Jump Parameters. Aut. Control Comp. Sci. 54, 1–9 (2020). https://doi.org/10.3103/S014641162001006X

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