{"title":"飞行座舱模拟器半自然建模复合体识别模块的开发","authors":"T. Tsibizova, N. V. Lukyanova, V. Klychnikov","doi":"10.1109/RusAutoCon49822.2020.9208100","DOIUrl":null,"url":null,"abstract":"A module was developed for the semi-natural modeling complex for the flight cockpit-simulator, which includes non-linear models of inertial navigation system errors, which improves the accuracy of simulated flight modes. A technique has been formed for assessing the accuracy of building models of measurement systems for a cockpit-simulator using data from a semi-natural experiment. A method has been developed to improve the accuracy of the modeling complex, based on the use of high-precision models built using the group method of data handling. The method for assessing the accuracy of the constructed models allows to select the model for each module of the semi-natural modeling complex.","PeriodicalId":101834,"journal":{"name":"2020 International Russian Automation Conference (RusAutoCon)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of an Identification Module of a Semi-Natural Modeling Complex for the Flight Cockpit- Simulator\",\"authors\":\"T. Tsibizova, N. V. Lukyanova, V. Klychnikov\",\"doi\":\"10.1109/RusAutoCon49822.2020.9208100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A module was developed for the semi-natural modeling complex for the flight cockpit-simulator, which includes non-linear models of inertial navigation system errors, which improves the accuracy of simulated flight modes. A technique has been formed for assessing the accuracy of building models of measurement systems for a cockpit-simulator using data from a semi-natural experiment. A method has been developed to improve the accuracy of the modeling complex, based on the use of high-precision models built using the group method of data handling. The method for assessing the accuracy of the constructed models allows to select the model for each module of the semi-natural modeling complex.\",\"PeriodicalId\":101834,\"journal\":{\"name\":\"2020 International Russian Automation Conference (RusAutoCon)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Russian Automation Conference (RusAutoCon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RusAutoCon49822.2020.9208100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Russian Automation Conference (RusAutoCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RusAutoCon49822.2020.9208100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of an Identification Module of a Semi-Natural Modeling Complex for the Flight Cockpit- Simulator
A module was developed for the semi-natural modeling complex for the flight cockpit-simulator, which includes non-linear models of inertial navigation system errors, which improves the accuracy of simulated flight modes. A technique has been formed for assessing the accuracy of building models of measurement systems for a cockpit-simulator using data from a semi-natural experiment. A method has been developed to improve the accuracy of the modeling complex, based on the use of high-precision models built using the group method of data handling. The method for assessing the accuracy of the constructed models allows to select the model for each module of the semi-natural modeling complex.