Кафедра автоматизації та енергоменеджменту

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Відповідальна за розділ: Тимошенко Наталія Анатоліївна, доцент кафедри автоматизації та енергоменеджменту аерокосмічного факультету. E-mail: n.tymoshenko@nau.edu.ua

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Browsing Кафедра автоматизації та енергоменеджменту by Author "Prochorenko, I"

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    Measuring Model of Helicopter’s Hovering Stabilization Parameters Against Point Objects
    (Electronics and control systems. – 2016. – №3(49). – С.121-125., 2016) Tymoshenko, N; Shevchuk, D; Prochorenko, I
    Here we explain measuring model of helicopter's hovering stabilization parameters against point object that requires smaller volume of calculation and preserves high speed and accuracy of stabilization. Also we investigate reduction of number of state vectors and volume of calculation via usage of extended Kalman filter and standard sensors.
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    Method of State Estimation and Identification of the Arial Vehicle under Destabilizing Action of Weather Conditions
    (IEEE 4th International Conference «Methods and Systems of Navigation and Motion Control» Conference Proceedings, 18-20 October 2016, Kyiv, Ukraine. – Р. 241-244., 2016) Tymoshenko, N; Shevchuk, D; Prochorenko, I
    Here we explain method and models for hover mode of aerial vehicle (helicopter) as well as measurements of parameters of this flight mode that requires smaller volume of calculation and preserves high speed and accuracy of stabilization. Also we investigate reduction of number of state vectors and volume of calculation via usage of extended Kalman filter and standard sensors.
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    Neural network model for predicting the level of residual knowledge of the subjects of study
    (Aviation in the XXI-st century. Safety in aviation and space technologies: the seventh world congress, 19-21 of september 2016: abstracts. – K., 2016. – V.1. – P. 1.1.4-1.1.6., 2016) Prochorenko, I; Tymoshenko, N; Galchenko, S
    The task is to build a neural network model depending on residual knowledge the trainees with whom they come into the labor market. Neural network model makes it possible with enough precision to predict the level of professional training according to their individual abilities.