{"title":"Determining the UAV State Space Rotational Dynamics Model Using Algebraic Inversion Technique","authors":"J. Muliadi, B. Kusumoputro","doi":"10.1145/3036331.3036355","DOIUrl":null,"url":null,"abstract":"Adequate models of UAV's dynamics were important for a successful aerial mission. Such adequate model of flight dynamics were required to assemble a good flight controller. For modeling purposes, the state space methods have been applied in various system dynamics. In the conventional modeling, the UAV's state space constructed from the first principle which involved efforts of measurement and deals with uncertainties and errors in sensors reading. Hence, this work proposes a simplified method to identify the UAV state space directly from its flight data. The flight data were directly used to overcome the uncertainties issues. As the conclusion, this method were able to ommit the requirement for moments of inertia measurement compared to previous technique of State Space modeling.","PeriodicalId":22356,"journal":{"name":"Tenth International Conference on Computer Modeling and Simulation (uksim 2008)","volume":"2014 1","pages":"52-56"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tenth International Conference on Computer Modeling and Simulation (uksim 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3036331.3036355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Adequate models of UAV's dynamics were important for a successful aerial mission. Such adequate model of flight dynamics were required to assemble a good flight controller. For modeling purposes, the state space methods have been applied in various system dynamics. In the conventional modeling, the UAV's state space constructed from the first principle which involved efforts of measurement and deals with uncertainties and errors in sensors reading. Hence, this work proposes a simplified method to identify the UAV state space directly from its flight data. The flight data were directly used to overcome the uncertainties issues. As the conclusion, this method were able to ommit the requirement for moments of inertia measurement compared to previous technique of State Space modeling.