Context. Military conflicts of the late XX-early XXI centuries are characterized by the using of a large number of new weapons, which allowed the warring parties to distance themselves as far as possible from the direct collision with each other. Unmanned aircraft apparatus (UAA) have become one of the latest weapons on the battlefield, which during military conflicts were proven to be more effective than manned planes, in conducting air reconnaissance and other combat tasks, as well as strike at the enemy. One of the ways to increase the efficiency of UAA is to increase the level of technical excellence of their control systems. Creating new approaches for designing navigation systems for unmanned aerial vehicles particular, based on a free-form inertial navigation system, is an urgent task, as it will allow automatic control of the UAA flight route in the absence of corrective signals from the global satellite navigation system. Objective. The purpose of this work is to develop a methodology for managing an unmanned aerial apparatus using an intelligent automatic control system. This technique will minimize the error of a free inertial navigation system due to the using of a fuzzy neural network system. The algorithm of the proposed method of constructing the intellectual system of automatic control of UAA navigation system using the fuzzy neural network apparatus in the MatLab 7 software environment was developed. A neural network training was conducted in the Python 3.6 software environment (Jupyter-notebook), as well as testing the UAA model in the robot operational system (ROS) simulator environment for comparison with existing methods. Method. To achieve this goal, the following methods were used: intelligent systems, the theory of automatic control, pseudospectral method; methods based on the genetic algorithm and apparatus of the fuzzy neural network. Results. The method of constructing the intelligent system of automatic control of an unmanned aerial apparatus for minimizing the error of a free-form inertial navigation system due to the application of the neural network has been developed. The work of the intellectual system of automatic control of the UAA navigational system using the neural network in the MatLab software environment based on the proposed implementation algorithm were tested. The possibility of practical application of the obtained results and comparison with traditional methods were investigated.
Context. Modern theory and practice of preparation and conduct of hostilities on land, at sea, in the air, and recently in cyberspace dictates the relentless modernization of military equipment. The development of fundamentally new weapons is carried out considering one of the main requirements – maximum automation of operational processes, which allows combatants to distance themselves from each other as much as possible. Among the newest models of armaments on the battlefield, due to the predominantly positional nature of the armed confrontation, unmanned aerial vehicles (UAVs) have become virtually indispensable due to their own multitasking. One of the ways to increase the efficiency of UAVs on the battlefield is to increase the level of technical perfection of flight control systems. Creating new approaches to the design of unmanned aerial vehicle navigation systems, in particular, based on a platformless inertial navigation system is an urgent task that will provide automatic control of the UAV flight route in the absence of corrective signals from the global satellite navigation system. Objective. The purpose of this work is to develop a method for improving the accuracy of MEMC navigation data processing of an inertial navigation system of an unmanned aerial vehicle based on an advanced Madgwik filter. This method will increase the speed of data processing of navigation parameters and the accuracy of determining the positioning parameters in the space of the UAV through the use of an advanced Madgwik filter. The paper shows the developed block diagram of MEMS PINS filtration on the basis of the improved Madgwik filter, the detailed mathematical description of filtration processes is carried out. This method was tested experimentally in the MATLAB software environment using a real set of data collected during the flight of the UAV. Method. To achieve this goal, the following methods were used: intelligent systems, theory of automatic control, pseudo-spectral method; methods based on genetic algorithm and fuzzy neural network apparatus. Results. A method for improving the accuracy of MEMC navigation data processing of an inertial navigation system of an unmanned aerial vehicle based on an advanced Madgwik filter has been developed. The possibility of practical application of the obtained results and in comparison, with traditional methods is investigated. An experiment was performed in the MatLab software environment, and a comparison was made with the method of processing navigation data based on the Madgwik filter and the Kalman filter. Conclusions. The developed method of increasing the accuracy of MEMC navigation data processing of an inertial navigation system of an unmanned aerial vehicle based on an advanced Madgwik filter shows an advantage over known methods in the absence of corrective signals from the global satellite navigation system for accuracy and speed of navigation data processing.
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