Using the computing module X-Plane in the development of a mathematical model of an unmanned aircraft
To date, rotary-wing unmanned aerial vehicles are widely used in various fields due to the proven versatility of this class of equipment, small dimensions, low thermal, acoustic and radar visibility, the ability to operate in conditions of significant overloads, and a wide temperature range, and the...
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description | To date, rotary-wing unmanned aerial vehicles are widely used in various fields due to the proven versatility of this class of equipment, small dimensions, low thermal, acoustic and radar visibility, the ability to operate in conditions of significant overloads, and a wide temperature range, and the ability to carry out off-airfield takeoff and landing. However, labor, financial and material costs for the creation of such devices are growing due to the complexity of flight tasks. Of particular importance here is the technical and economic risk associated with possible engineering errors, manifestations of hidden defects that were not detected during testing, etc. To reduce the likelihood of these adverse events, considering the time spent and the cost of design, an integrated approach is needed to cover all aspects of the development and operation of an unmanned aerial complex. The solution to this problem is possible through an organic combination of traditional and progressive highly informative methods. One of the successfully used approaches is automated mathematical modeling of aircraft dynamics at various stages of flight. The results obtained in the course of computer tests are used for operational verification and debugging of flight control system algorithms, serving as initial indicative indicators of flight performance and operational characteristics, allowing to significantly speed up the development process at the early stages. This article discusses an alternative simulation option using the MATLAB Simulink software package and the X-Plane flight simulator computational module on the example of an unmanned aerial vehicle of a coaxial helicopter type. This method is compared with the classical approach to mathematical modeling of vehicle dynamics. Information interaction is implemented between the control system loops and the modeling environment for the purposes of operational analysis of flight information. Verification of the developed mathematical model is carried out by comparing the results of computer tests with the data obtained during field tests of the prototype. |
doi_str_mv | 10.1063/5.0152056 |
format | Conference Proceeding |
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However, labor, financial and material costs for the creation of such devices are growing due to the complexity of flight tasks. Of particular importance here is the technical and economic risk associated with possible engineering errors, manifestations of hidden defects that were not detected during testing, etc. To reduce the likelihood of these adverse events, considering the time spent and the cost of design, an integrated approach is needed to cover all aspects of the development and operation of an unmanned aerial complex. The solution to this problem is possible through an organic combination of traditional and progressive highly informative methods. One of the successfully used approaches is automated mathematical modeling of aircraft dynamics at various stages of flight. The results obtained in the course of computer tests are used for operational verification and debugging of flight control system algorithms, serving as initial indicative indicators of flight performance and operational characteristics, allowing to significantly speed up the development process at the early stages. This article discusses an alternative simulation option using the MATLAB Simulink software package and the X-Plane flight simulator computational module on the example of an unmanned aerial vehicle of a coaxial helicopter type. This method is compared with the classical approach to mathematical modeling of vehicle dynamics. Information interaction is implemented between the control system loops and the modeling environment for the purposes of operational analysis of flight information. Verification of the developed mathematical model is carried out by comparing the results of computer tests with the data obtained during field tests of the prototype.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0152056</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Aircraft ; Algorithms ; Environment models ; Field tests ; Flight characteristics ; Flight control systems ; Flight simulators ; Helicopters ; Mathematical analysis ; Mathematical models ; Modules ; Task complexity ; Unmanned aerial vehicles ; Unmanned aircraft ; Verification</subject><ispartof>AIP conference proceedings, 2023, Vol.2833 (1)</ispartof><rights>Author(s)</rights><rights>2023 Author(s). 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However, labor, financial and material costs for the creation of such devices are growing due to the complexity of flight tasks. Of particular importance here is the technical and economic risk associated with possible engineering errors, manifestations of hidden defects that were not detected during testing, etc. To reduce the likelihood of these adverse events, considering the time spent and the cost of design, an integrated approach is needed to cover all aspects of the development and operation of an unmanned aerial complex. The solution to this problem is possible through an organic combination of traditional and progressive highly informative methods. One of the successfully used approaches is automated mathematical modeling of aircraft dynamics at various stages of flight. The results obtained in the course of computer tests are used for operational verification and debugging of flight control system algorithms, serving as initial indicative indicators of flight performance and operational characteristics, allowing to significantly speed up the development process at the early stages. This article discusses an alternative simulation option using the MATLAB Simulink software package and the X-Plane flight simulator computational module on the example of an unmanned aerial vehicle of a coaxial helicopter type. This method is compared with the classical approach to mathematical modeling of vehicle dynamics. Information interaction is implemented between the control system loops and the modeling environment for the purposes of operational analysis of flight information. Verification of the developed mathematical model is carried out by comparing the results of computer tests with the data obtained during field tests of the prototype.</description><subject>Aircraft</subject><subject>Algorithms</subject><subject>Environment models</subject><subject>Field tests</subject><subject>Flight characteristics</subject><subject>Flight control systems</subject><subject>Flight simulators</subject><subject>Helicopters</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Modules</subject><subject>Task complexity</subject><subject>Unmanned aerial vehicles</subject><subject>Unmanned aircraft</subject><subject>Verification</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotUMlKxEAUbETBOHrwDxq8CRlf78lRBjcY0MMIc2s6vWiGpDtmEfx7M8vlFa-q3kIhdEtgSUCyB7EEIigIeYYyIgTJlSTyHGUAJc8pZ9tLdDUMOwBaKlVkyH8OdfzC47fHNrXdNO67Nrmp8XibfzQmelzHg-78r29S1_o44hSwwa2Z6bnU1jT7Gd8c-Iin2JoYvcOm7m1vwniNLoJpBn9zwgXaPD9tVq_5-v3lbfW4zrtS0pwE68tASai4FMyCASKNKHwlgRKnuJIFB2FVYKq0ztCSMu4q5pySnHNi2QLdHdd2ffqZ_DDqXZr6OF_UtFBMAmNcza77o2uw9Th_n6Lu-ro1_Z8moPcpaqFPKbJ_mHZjog</recordid><startdate>20231006</startdate><enddate>20231006</enddate><creator>Serebrenny, Vladimir Valerievich</creator><creator>Alkhanov, Daniil Sergeevich</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20231006</creationdate><title>Using the computing module X-Plane in the development of a mathematical model of an unmanned aircraft</title><author>Serebrenny, Vladimir Valerievich ; Alkhanov, Daniil Sergeevich</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p962-1fce9f21fb4653c0a016a58eb6021d74768405c7f379cda29234db3dd764441c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aircraft</topic><topic>Algorithms</topic><topic>Environment models</topic><topic>Field tests</topic><topic>Flight characteristics</topic><topic>Flight control systems</topic><topic>Flight simulators</topic><topic>Helicopters</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Modules</topic><topic>Task complexity</topic><topic>Unmanned aerial vehicles</topic><topic>Unmanned aircraft</topic><topic>Verification</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Serebrenny, Vladimir Valerievich</creatorcontrib><creatorcontrib>Alkhanov, Daniil Sergeevich</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Serebrenny, Vladimir Valerievich</au><au>Alkhanov, Daniil Sergeevich</au><au>Romanova-Bolshakova, Irina K.</au><au>Karapetyan, Aida S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Using the computing module X-Plane in the development of a mathematical model of an unmanned aircraft</atitle><btitle>AIP conference proceedings</btitle><date>2023-10-06</date><risdate>2023</risdate><volume>2833</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>To date, rotary-wing unmanned aerial vehicles are widely used in various fields due to the proven versatility of this class of equipment, small dimensions, low thermal, acoustic and radar visibility, the ability to operate in conditions of significant overloads, and a wide temperature range, and the ability to carry out off-airfield takeoff and landing. However, labor, financial and material costs for the creation of such devices are growing due to the complexity of flight tasks. Of particular importance here is the technical and economic risk associated with possible engineering errors, manifestations of hidden defects that were not detected during testing, etc. To reduce the likelihood of these adverse events, considering the time spent and the cost of design, an integrated approach is needed to cover all aspects of the development and operation of an unmanned aerial complex. The solution to this problem is possible through an organic combination of traditional and progressive highly informative methods. One of the successfully used approaches is automated mathematical modeling of aircraft dynamics at various stages of flight. The results obtained in the course of computer tests are used for operational verification and debugging of flight control system algorithms, serving as initial indicative indicators of flight performance and operational characteristics, allowing to significantly speed up the development process at the early stages. This article discusses an alternative simulation option using the MATLAB Simulink software package and the X-Plane flight simulator computational module on the example of an unmanned aerial vehicle of a coaxial helicopter type. This method is compared with the classical approach to mathematical modeling of vehicle dynamics. Information interaction is implemented between the control system loops and the modeling environment for the purposes of operational analysis of flight information. 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identifier | ISSN: 0094-243X |
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language | eng |
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source | AIP Journals Complete |
subjects | Aircraft Algorithms Environment models Field tests Flight characteristics Flight control systems Flight simulators Helicopters Mathematical analysis Mathematical models Modules Task complexity Unmanned aerial vehicles Unmanned aircraft Verification |
title | Using the computing module X-Plane in the development of a mathematical model of an unmanned aircraft |
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