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Synthesis of Suboptimal Filters for Multivariable Multicriteria Discrete Systems

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Abstract

We consider the problem of constructing suboptimal filters (lower-order optimal filters, i.e., filters for linear vector functionals of the system state vector) for stochastic multivariable multicriteria plants. The method for constructing such filters is presented in the Luenberger canonical basis. Using a numerical example of a seventh-order system, we show that the proposed approach improves the optimality of filters compared to filters based on scalar observers.

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Funding

This work was supported by the Ministry of Science and Higher Education of the Russian Federation within the framework of the program of the Moscow Center for Fundamental and Applied Mathematics under agreement no. 075-15-2022-284 and by the Russian Foundation for Basic Research, project nos. 20-37-90065-Postgraduates and 20-08-00073-A.

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Authors and Affiliations

  1. Department of Mathematics, School of Science, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310005, China

    V. V. Fomichev

  2. Lomonosov Moscow State University, Moscow, 119991, Russia

    V. V. Fomichev & M. A. Kamenshchikov

  3. Federal Research Center “Computer Science and Control,” Russian Academy of Sciences, Moscow, 119333, Russia

    V. V. Fomichev

  4. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, 117997, Russia

    M. A. Kamenshchikov

  5. National University of Science and Technology “MISiS”, Moscow, 119049, Russia

    M. A. Kamenshchikov

Authors
  1. V. V. Fomichev
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  2. M. A. Kamenshchikov
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Corresponding authors

Correspondence to V. V. Fomichev or M. A. Kamenshchikov.

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Translated by V. Potapchouck

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Fomichev, V.V., Kamenshchikov, M.A. Synthesis of Suboptimal Filters for Multivariable Multicriteria Discrete Systems. Diff Equat 58, 1097–1104 (2022). https://doi.org/10.1134/S0012266122080109

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  • DOI: https://doi.org/10.1134/S0012266122080109

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