Sučasnì Informacìjnì Tehnologìï u Sferì Bezpeki ta Oboroni (Sep 2020)

METHOD FOR FORMALIZING KNOWLEDGE ABOUT THE PROCESSES OF DETERMINING PERFECT FLIGHT STRATEGIES FOR UNMANNED VEHICLES DURING PREPARATION FOR AERIAL SURVEILLANCE BASED ON FUZZY LOGICAL SYSTEMS

  • Oleksandr Permiakov,
  • Marina Dudko,
  • Natalia Korolyuk

DOI
https://doi.org/10.33099/2311-7249/2020-38-2-12-20
Journal volume & issue
Vol. 38, no. 2
pp. 12 – 20

Abstract

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The article proposes an approach to the formalization of knowledge about the process of determining an appropriate flight strategy for an unmanned aerial vehicle at the stage of planning aerial reconnaissance using Hebrew-contiguous methods, which are the best in terms of taking into account practice, experience, intuition, knowledge of decision-makers , when conducting aerial reconnaissance, and are looking for solutions within some pidpros-tor of possible acceptable solutions. The developed method allows one to formalize factors, takes into account the tactical conditions of aerial reconnaissance, the influence of the external environment on the flight range of an unmanned aerial vehicle in the form of linguistic and interval-estimated parameters for each option, which allow for uncertainty. The initial data of the method is a recommendation regarding an expedient flight strategy for an unmanned aerial vehicle, containing information on the list of the most important reconnaissance objects, the start point, the end of the flight route, the initial flight path, the recommended flight altitudes in dangerous areas, the method search and inspection of miscevoste. Based on the structure of fuzzy production rules by the MISO-structure, in the conclusion of which real numbers (the number of the expedient strategy for the flight of an unmanned aerial vehicle) are used, which is proposed as a fuzzy inference algorithm in a fuzzy logical system of interval type 2 for derivation of inference for fuzzy sets of the second order. It is substantiated that the components of the architecture of a fuzzy logical system of interval type 2 provide the implementation of the corresponding inference mechanism, which is a set of inference rules and methods of their application.

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