Determining the UAV state space rotational dynamics model using algebraic inversion technique

Jemie Muliadi, Benyamin Kusumo Putro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Computer Modeling and Simulation, ICCMS 2017
PublisherAssociation for Computing Machinery
Pages52-56
Number of pages5
ISBN (Electronic)9781450348164
DOIs
Publication statusPublished - 20 Jan 2017
Event8th International Conference on Computer Modeling and Simulation, ICCMS 2017 - Canberra, Australia
Duration: 20 Jan 201723 Jan 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F128047

Conference

Conference8th International Conference on Computer Modeling and Simulation, ICCMS 2017
CountryAustralia
CityCanberra
Period20/01/1723/01/17

Keywords

  • Linearized Newton-euler equation
  • Quadrotor modeling
  • State space identification
  • UAV

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  • Cite this

    Muliadi, J., & Putro, B. K. (2017). Determining the UAV state space rotational dynamics model using algebraic inversion technique. In Proceedings of the 8th International Conference on Computer Modeling and Simulation, ICCMS 2017 (pp. 52-56). (ACM International Conference Proceeding Series; Vol. Part F128047). Association for Computing Machinery. https://doi.org/10.1145/3036331.3036355