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Izvestiya SFedU
Engineering sciences
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ISSN 1999-9429 print
ISSN 2311-3103 online
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  • AIRCRAFT FLIGHT PATH PREDICTION UNDER COMPLETE PARAMETRIC UNCERTAINTY

    V.V. Kosyanchuk, V.V. Glasov, E.Y. Zybin, Liguo Tan
    2021-04-04
    Abstract ▼

    Most of the methods for predicting the behavior of dynamic systems are based on the information
    about the parameters of their mathematical models. However, the problems of
    nonstationarity, nonlinearity and nonidentifiability of models of real complex systems lead to the
    fact that traditional parametric methods are applicable in practice only when the parameters and
    structure of models of systems are reliably known, and the uncertainties in the formulation of the
    problem are significantly limited. The article describes an original nonparametric method for
    predicting the aircraft flight path under absence of a priori information about the parameters of its
    mathematical flight dynamics model. The proposed method, unlike similar widely known ones,
    does not use logical or statistical calculations and does not require its preliminary training or
    long-term tuning. It is based only on the basis of a retrospective analysis of several sequential
    values of the spatial coordinates of the aircraft and its control signals, therefore it is not subject to
    model errors and can be used to predict the flight path of the aircraft under complete parametric
    uncertainty, even in the case of non-identifiability of its flight dynamics model. The results of numerical
    simulation of the solution to the problem of predicting the flight path of an unmanned
    aerial vehicle of the most common type of quadrocopter under complete uncertainty in parameters
    of its mathematical model are presented. The results obtained confirm the efficiency of the developed
    method and show high performances of the accuracy of solving the problem and the speed of
    tuning the algorithm. The described approach can be used to predict the motion path of any other
    vehicle (car, ship, etc.), if its model is linearizable over the observed time interval and there is
    information about its control signals. Practical implementation of the described nonparametric
    method together with traditional parametric ones will improve the accuracy of flight path predicting
    and solve the problem of high-precision landing of an unmanned aerial vehicle on an actively
    maneuvering ship, and specifically in the event of various critical situations.

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