Systems and Means of Informatics
2025, Volume 35, Issue 1, pp 41-58
NORMAL SUBOPTIMAL FILTERING METHODS IN IMPLICIT OBSERVABLE GAUSSIAN STOCHASTIC SYSTEMS
Abstract
The article is dedicated to the theory of normal suboptimal filters (NSOF) and modified NSOF (MNSOF) for Gaussian continuous and discrete implicit stochastic systems (StS) reducible to explicit. It is supposed that observations do not influence the observable object and are described by explicit stochastic differential and difference equations. A short survey in the field of suboptimal NSOF (MNSOF) synthesis is given. Basic algorithms of NSOF (MNSOF) for the first type synthesis for nonlinear and quasi-linear reducible StS with smooth and nonsmooth implicit nonlinearities are described. The theory of NSOF of the second type for reducible implicit StS is developed on the basis of generalized Kalman-Bucy and Kalman filters. Such NSOF unlike NSOF (MNSOF) of the first type do not permit to estimate accuracy of filtering beforehand applications: quick (or real-time) information processing in technical or organization-technical-economical systems is described by small dimension equations when it is possible to neglect time constants at high derivatives (differences). The results are also applicable to implicit hereditary StS reducible to explicit differential (discrete) StS. Directions for future research are formulated.
[+] References (17)
- Sinitsyn, I. N. 2007. Fil'try Kalmana i Pugacheva [Kalman and Pugachev filters]. 2nd ed. Moscow: Logos. 776 p.
- Sinitsyn, I. N. 2017. Parametricheskoe analiticheskoe modelirovanie protsessov v stokhasticheskikh sistemakh, ne razreshennykh otnositel'no proizvodnykh [Parametric analytical modeling of wide band processes in stochastic systems with unsolved derivatives]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 27(1):20{45. doi: 10.14357/08696527170102. EDN: YODCZL.
- Sinitsyn, I. N. 2021. Normal'nye suboptimal'nye fil'try dlya differentsial'nykh stokhasticheskikh sistem, ne razreshennykh otnositel'no proizvodnykh [Normal suboptimal filtering for differential stochastic systems with unsolved derivatives]. Informatika i ee Primeneniya - Inform. Appl. 15(1):3{10. doi: 10.14357/19922264210101. EDN: UPEHRI.
- Sinitsyn, I. N. 2021. Analytical modeling and estimation of normal processes defined by stochastic differential equations with unsolved derivatives. J. Mathematics Statistics Research 3(1): 139. 7 p. doi: 10.36266/JMSR/139.
- Sinitsyn, I. N. 2021. Theory of control stochastic systems with unsolved derivatives. Automation and control. Theories and applications. Ed. E. Dadios. IFSA Publishing S. L. 59G17. doi: 10.5772/intechopen.100448.
- Sinitsyn, I. N. 2022. Analiticheskoe modelirovanie i otsenivanie nestatsionarnykh normal'nykh protsessov v stokhasticheskikh sistemakh, ne razreshennykh otnositel'no proizvodnykh [Analytical modeling and estimation of nonstationary normal processors with unsolved derivatives]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 32(2):58{71. doi: 10.14357/08696527220206. EDN: YMGERJ.
- Sinitsyn, I. N. 2024. Suboptimal'naya fil'tratsiya v stokhasticheskikh sistemakh, ne razreshennykh otnositel'no proizvodnykh, so sluchaynymi parametrami [Suboptimal filtering in stochastic systems with random parameters and unsolved derivatives]. Informatika i ee Primeneniya - Inform. Appl. 18(1):2{10. doi: 10.14357/ 19922264240101. EDN: KUWMKJ.
- Evlanov, A.G., and V. M. Konstantinov. 1976. Sistemy so slozhnymi parametrami [Systems with random parameters]. Moscow: Nauka. 568 p.
- Krasovskskiy, A. A., ed. 1987. Spravochnik po teorii avtomaticheskogo upravleniya [Handbook for automatic control]. Moscow: Nauka. 712 p.
- Aleksandrovskaya, L.N., I. Z. Aronov, V.I. Kruglov, et al. 2008. Bezopasnost' i nadezhnost' tekhnicheskikh sistem [Security and safety of technical systems]. Moscow: Universitetskaya kniga, Logos. 375 p.
- Sinitsyn, I. N., and A. S. Shalamov. 2019. Lektsii po teorii sistem integrirovannoy logisticheskoy podderzhki [Lectures on theory of integrated logistic support systems]. 2nd ed. Moscow: TORUS PRESS. 1072 p. END: HVAZTX.
- Kolmanovskiy, V. B., and V. R. Nosov. 1981. Ustoychivost' i periodicheskie rezhimy reguliruemykh sistem s posledeystviem [Stability and periodic modes of regulated systems with aftereffects]. Moscow: Nauka. 448 p.
- Azbelev, N. V., V. P. Maksimov, and L.F. Rakhmatulina. 1991. Vvedenie v teoriyu funktsional'no-differentsial'nykh uravneniy [Introduction to the theory of functional differential equations]. Moscow: Nauka. 277 p.
- Bosov, A. V. 2023. Issledovanie robastnosti chislennykh approksimatsiy fil'tra Vonema [Robustness investigation of the numerical approximation of the Wonham filter]. Informatika i ee Primeneniya - Inform. Appl. 17(2):41{49. doi: 10.14357/ 19922264230206. EDN: BGILKR.
- Bosov, A. V. 2023. Optimal'naya fil'tratsiya sostoyaniya nelineynoy dinamicheskoy sistemy po nablyudeniyam so sluchaynymi zapazdyvaniyami [Nonlinear dynamic system state optimal filtering by observations with random delays]. Informatika i ee Primeneniya - Inform. Appl. 17(3):8-17. doi: 10.14357/19922264230302. EDN: CFVYJM.
- Bosov, A. V. 2023. Observation-based filtering of state of a nonlinear dynamical system with random delays. Automat. Rem. Contr. 84(6):594-605. doi: 10/1134/ S0005117923060036. EDN: GVWEAB.
- Sinitsyn, I. N. 2023. Kanonicheskie predstavleniya sluchaynykh funktsiy. Teoriya i primeneniya [Canonical expansion of random functions. Theory and application]. 2nd ed. Moscow: TORUS PRESS. 816 p. doi: 10.30826/94588-308-6. EDN: XHBITA.
[+] About this article
Title
NORMAL SUBOPTIMAL FILTERING METHODS IN IMPLICIT OBSERVABLE GAUSSIAN STOCHASTIC SYSTEMS
Journal
Systems and Means of Informatics
Volume 35, Issue 1, pp 41-58
Cover Date
2025-04-20
DOI
10.14357/08696527250102
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
Gaussian stochastic system (StS); implicit StS; modificated NSOF (MNSOF); normal suboptimal filter (NSOF) of the first and second types
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
 Moscow State Aviation Institute (National Research University), 4 Volokolamskoe Shosse, Moscow 125933, Russian Federation
|