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Sequential Improvement Method in Probabilistic Criteria Optimization Problems for Linear-in-State Jump Diffusion Systems

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Abstract

Here we study the problems of probabilistic and quantile optimization of multidimensional controllable jump diffusion. As the main tool we use Chebyshev-type probability estimates. With them the problems under consideration are reduced to one auxiliary deterministic optimal control problem in terms of the moment characteristics of the process. To find its solution, we use Krotov’s global improvement method.

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Funding

Sections 4, 6, and 8 were written by K.A. Tsarkov at the expense of Russian Science Foundation project no. 22-11-00042; https://rscf.ru/project/22-11-00042 at ICS RAS.

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Authors and Affiliations

  1. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

    M. M. Khrustalev & K. A. Tsarkov

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  1. M. M. Khrustalev
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  2. K. A. Tsarkov
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Correspondence to M. M. Khrustalev or K. A. Tsarkov.

Additional information

This paper was recommended for publication by A.I. Kibzun, a member of the Editorial Board

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Khrustalev, M.M., Tsarkov, K.A. Sequential Improvement Method in Probabilistic Criteria Optimization Problems for Linear-in-State Jump Diffusion Systems. Autom Remote Control 84, 626–640 (2023). https://doi.org/10.1134/S0005117923060061

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  • DOI: https://doi.org/10.1134/S0005117923060061

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