Radial basis function neural network based PID control for quad-rotor flying robot

Shoji Furukawa, Shunya Kondo, Atsuo Takanishi, Hun Ok Lim

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

    2 Citations (Scopus)

    Abstract

    It is difficult for flying robots with a conventional PID controller to fly stably with external disturbances such as wind. Thus, a flight control method that can change the control parameters of a conventional PID controller according to the external disturbances is described in this paper. The control parameters of the PID controller are automatically adjusted based on a radial basis function neural network (RBFNN). The experimental results show that the control method is capable of effectively dealing with external disturbances.

    Original languageEnglish
    Title of host publicationICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings
    PublisherIEEE Computer Society
    Pages580-584
    Number of pages5
    Volume2017-October
    ISBN (Electronic)9788993215137
    DOIs
    Publication statusPublished - 2017 Dec 13
    Event17th International Conference on Control, Automation and Systems, ICCAS 2017 - Jeju, Korea, Republic of
    Duration: 2017 Oct 182017 Oct 21

    Other

    Other17th International Conference on Control, Automation and Systems, ICCAS 2017
    CountryKorea, Republic of
    CityJeju
    Period17/10/1817/10/21

    Keywords

    • Flight control
    • Flying robot
    • Propellers
    • Quad-rotor
    • RBF neural network

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Control and Systems Engineering
    • Electrical and Electronic Engineering

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  • Cite this

    Furukawa, S., Kondo, S., Takanishi, A., & Lim, H. O. (2017). Radial basis function neural network based PID control for quad-rotor flying robot. In ICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings (Vol. 2017-October, pp. 580-584). IEEE Computer Society. https://doi.org/10.23919/ICCAS.2017.8204300