In this work, we propose to use a methodology based on an identification and control scheme using recurrent high-order neural networks (RHONNs) trained online with an unscented Kalman filter (UKF) based algorithm. Initial parameters for the UKF are selected employing two bio-inspired algorithms: Bat Algorithm (BA) and Grey Wolf Optimizer (GWO). The controller design includes sliding modes techniques for trajectory tracking of the 7 degrees of freedom (DOF) Mitsubishi PA10-7CE robotic arm.


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    Titel :

    A bio-inspired optimization approach for trajectory tracking of robotic arms.


    Beteiligte:


    Erscheinungsdatum :

    05.12.2022


    Format / Umfang :

    1208208 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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