ПРОГНОЗИРОВАНИЕ ТРАЕКТОРИИ ПОЛЕТА ЛЕТАТЕЛЬНОГО АППАРАТА В УСЛОВИЯХ ПОЛНОЙ ПАРАМЕТРИЧЕСКОЙ НЕОПРЕДЕЛЕННОСТИ

Abstract

Most of the methods for predicting the behavior of dynamic systems are based on the informationabout the parameters of their mathematical models. However, the problems ofnonstationarity, nonlinearity and nonidentifiability of models of real complex systems lead to thefact that traditional parametric methods are applicable in practice only when the parameters andstructure of models of systems are reliably known, and the uncertainties in the formulation of theproblem are significantly limited. The article describes an original nonparametric method forpredicting the aircraft flight path under absence of a priori information about the parameters of itsmathematical 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 orlong-term tuning. It is based only on the basis of a retrospective analysis of several sequentialvalues of the spatial coordinates of the aircraft and its control signals, therefore it is not subject tomodel errors and can be used to predict the flight path of the aircraft under complete parametricuncertainty, even in the case of non-identifiability of its flight dynamics model. The results of numericalsimulation of the solution to the problem of predicting the flight path of an unmannedaerial vehicle of the most common type of quadrocopter under complete uncertainty in parametersof its mathematical model are presented. The results obtained confirm the efficiency of the developedmethod and show high performances of the accuracy of solving the problem and the speed oftuning the algorithm. The described approach can be used to predict the motion path of any othervehicle (car, ship, etc.), if its model is linearizable over the observed time interval and there isinformation about its control signals. Practical implementation of the described nonparametricmethod together with traditional parametric ones will improve the accuracy of flight path predictingand solve the problem of high-precision landing of an unmanned aerial vehicle on an activelymaneuvering ship, and specifically in the event of various critical situations.