Browsing by Author "Tymoshenko, N"

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    Intelligent Control System Against Aircraft’s Structural Damage in the Flight
    (IEEE 4th International Conference «Methods and Systems of Navigation and Motion Control» Conference Proceedings, 18-20 October 2016, Kyiv, Ukraine. – Р. 241-244., 2016) Shevchuk, D; Tymoshenko, N
    In this paper, intelligent flight control system for recovering controllability of the aircraft when an unexpected problem (such as faults or failures to the actuators/sensors or structural damage) occurs during a flight is proposed.
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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.
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    Synthesis of an Intelligent UAV Control System Based on Fuzzy Logic in External Disturbance Conditions
    (Journal of Automation, Mobile Robotics and Intelligent Systems, 2020-12) Shevchuk, D; Prokhorenko, I; Tymoshenko, N; Korobiichuk, I
    To ensure reliable execution of flight tasks in the presence of both external perturbations and internal parametric perturbations, deterioration of the characteristics of the sensors, a control system structure based on intelligent technologies is proposed. The process of forming a “knowledge base” of a fuzzy controller is considered. The results of mathematical modeling of the longitudinal UAV control channel with a PID-controller and a fuzzy controller in the control loop are presented.