Systems and Means of Informatics
2024, Volume 34, Issue 2, pp 3-20
CONDITIONALLY-OPTIMAL FILTRATION AND CONTROL FOR STOCHASTIC SYSTEMS WITH RANDOM PARAMETERS AND UNSOLVED DERIVATIVES
Abstract
Methodological support for synthesis of conditionally: optimal filtering and control for continuous, discrete, and continuous-discrete stochastic systems with unsolved derivatives (StS USD) and random parameters is developed. A survey of conditionally-optimal filtering (COF) and conditionally optimal control (COC) is presented. It is supposed that random parameters are described by multicomponent integral canonical expansions (MC ICE). Synthesis of COF and COC is based on Pugachev's COC concepts. Special attention is paid to the three COC typical problems in the case of local criteria. Applications: nonlinear correlational estimation of potential and instrumental accuracy of COF and COC at nonstationary impact disturbances in StS USD. An illustrative example is given. Future research is connected with effects of disturbances accumulation, drifts, and excurtions based on finite dimension distribution of stochastic processes.
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[+] About this article
Title
CONDITIONALLY-OPTIMAL FILTRATION AND CONTROL FOR STOCHASTIC SYSTEMS WITH RANDOM PARAMETERS AND UNSOLVED DERIVATIVES
Journal
Systems and Means of Informatics
Volume 34, Issue 2, pp 3-20
Cover Date
2024-05-20
DOI
10.14357/08696527240201
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
conditionally optimal control (COC); conditionally optimal filtering (COF); multicomponent integral canonical expansions (MC ICE); random parameters; stochastic systems with unsolved derivatives (StS USD)
Authors
I. N. Sinitsyn 
Author Affiliations
Federal Research Center "Computer Science and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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