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Synthesis of Stochastic Optimal Control Based on Nonlinear Probabilistic Criteria

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Abstract

Method of synthesis of control of stochastic processes is considered. Compared to the known approaches, the proposed method provides significantly more efficient process control by optimizing according to criteria that are nonlinearly dependent on the density of the distribution of the process and not on its particular characteristics (expectation, variance, etc.). The procedure for its computational implementation has been developed. A numerical example of optimal control synthesis illustrating the effectiveness of the proposed method is given. The advantageous features of the developed approach provide the possibility of its wide practical application in modern and promising information and control systems.

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Authors and Affiliations

  1. Rostov State University of Economics, Rostov-on-Don, Russia

    Boris Klepfish

  2. Moscow Technical University of Communications and Informatics – North Caucasus Branch, Rostov-on-Don, Russia

    Sergey Sokolov & Marianna Polyakova

Authors
  1. Boris Klepfish
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  2. Sergey Sokolov
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  3. Marianna Polyakova
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Corresponding authors

Correspondence to Sergey Sokolov or Marianna Polyakova.

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The authors declare that they have no conflicts of interest.

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Boris Klepfish, Sokolov, S. & Polyakova, M. Synthesis of Stochastic Optimal Control Based on Nonlinear Probabilistic Criteria. Aut. Control Comp. Sci. 56, 421–427 (2022). https://doi.org/10.3103/S0146411622050066

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  • DOI: https://doi.org/10.3103/S0146411622050066

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