Модель вимірів параметрів стабілізації висіння гелікоптера відносно точкових об'єктів

Here we explain measuring model of helicopter's hovering stabilization parameters againstpoint object that requires smaller volume of calculation and preserves high speed and accuracy ofstabilization. Also we investigate reduction of number of state vectors and volume of calculation viausage of extended Kalman filter and standard sensorsОбоснована модель измерений параметров стабилизации висения вертолета относительно точечных объектов, которая требует меньшего объема вычислений и сохраняет высокую скорость и точность стабилизации. Исследована возможность сокращения векторов состояния и измерений за счет использования расширенного фильтра Калмана и штатных измерителейОбґрунтовано модель вимірів параметрів стабілізації висіння гелікоптера відносно точкових об’єктів, яка вимагає меншого обсягу обчислень і зберігає високу швидкість і точність стабілізації. Досліджено можливість скорочення векторів стану та вимірювань за рахунок використання розширеного фільтра Калмана та штатних вимірювачі

Method of State Estimation and Identification of the Arial Vehicle under Destabilizing Action of Weather Conditions

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

Measuring Model of Helicopter’s Hovering Stabilization Parameters Against Point Objects

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

Neural network model for predicting the level of residual knowledge of the subjects of study

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

Measuring Model of Helicopter’s Hovering Stabilization Parameters Against Point Objects

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

Neural network model for predicting the level of residual knowledge of the subjects of study

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

Method of State Estimation and Identification of the Arial Vehicle under Destabilizing Action of Weather Conditions

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