Certificate of Registration Media number Эл #ФС77-53688 of 17 April 2013. ISSN 2308-6033. DOI 10.18698/2308-6033
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Directions for control operations intellectualization applicable for operational space flight control

Published: 14.11.2018

Authors: Soloviev S.V.

Published in issue: #11(83)/2018

DOI: 10.18698/2308-6033-2018-11-1824

Category: Aviation and Rocket-Space Engineering | Chapter: Aircraft Dynamics, Ballistics, Motion Control

The paper focuses on some particularities of the present system of control over implementation of flight operations and space vehicle condition. The study gives the examples of the most effective application of artificial intelligence in logical games. Promising directions of control operations intellectualization applicable for efficient space flight control were presented. Contemporary methods of intellectual analysis in different fields were considered. As a result, we suggested the directions of intellectualization which are the most satisfying for creating the base of prospective software applications for analysis of telemetric information with the use of special mathematical apparatus. Stated principles of using cluster and wavelet analysis for automatization of tendency detecting process are directed to solve control missions and space vehicles condition predicting

[1] Soloviev V.А., Lysenko L.N., Lyubinskiy V.E. Upravlenie kosmicheskimi poletami [Space flight control]. Moscow, BMSTU Publ., 2009, 446 p.
[2] Аverkin А.N., Gaaze-Rapoport M.G., Pospelov D.А. Tolkovyy slovar po iskusstvennomu intellektu [Artificial intelligence explanatory dictionary]. Moscow, Radio i svyaz Publ., 1992, 256 p.
[3] Campbell M., Hoane A.J., Jr., Feng-Hsiung Hsu. Deep Blue. Artificial Intelligence, 2002, vol. 134, no. 1, pp. 57–83. DOI: 10.1016/S0004-3702(01)00129-1
[4] Аrlazarov V.L. Аlgoritmy shakhmatnykh programm [Chess software algorithms]. Available at: (accessed November 21, 2017).
[5] Burger C. Google DeepMind’s AlphaGo: How it works. On Personalization and Data. Available at: (accessed October 20, 2017).
[6] Hassabis D. Kak rabotaet iskusstvenny intellekt (II) DeepMind [How artificial intelligence (AI) DeepMind works]. Available at: (accessed November 1, 2017).
[7] Soloviev S.V. Inzhenernyy zhurnal: nauka i innovatsii — Engineering Journal: Science and Innovation, 2016, issue 2 (50). DOI: 10.18698/2308-6033-2016-2-1469
[8] Wertz J.R., Puschell J.J., Everett D.F. Space mission engineering: The new SMAD. Microcosm corp., 2011, 1033 p.
[9] Fortescue P., Stark J., Swinerd G. Spacecraft Systems Engineering. Wiley Publ., 2011, 724 p. [In Russ.: Fortescue P., Stark J., Swinerd G. Razrabotka sistem kosmicheskikh apparatov. Moscow, Аlpina Pablisher Publ., 2017, 764 p.].
[10] Soloviev S.V., Khairov K.I. Metod prognozirovaniya sostoyaniya kosmicheskikh apparatov na osnove intellektualnogo analiza dannykh [Prediction method for space vehicles condition on the basis of intellectual analysis of data]. Trudy XIX mezhdunarodnoy konferentsii «Problemy upravleniya i modelirovaniya v slozhnykh sistemakh» [Proc. of 19th International Conference “Problems of control and simulation in complex systems”]. 2017, pp. 218–223.
[11] Аbramov N.S., Talalaev А.А., Fralenko V.P. Informatsionnye tekhnologii i vychislitelnye sistemy — Journal of Information Technologies and Computing Systems, 2016, no. 1, pp. 64–75.
[12] Lukashin Y.P. Аdaptivnye metody kratkosrochnogo prognozirovaniya vremennykh ryadov [Adaptive methods of short-time predictioms of timing series]. Moscow, Finansy i statistika Publ., 2003, 415 p.