The adoption of DC drives in agricultural applications addresses the need for efficient, precise, and reliable control of machinery, contributing to the advancement of modern farming techniques and sustainable agricultural practices. To meet these needs, the proposed system utilizes a solar-powered Cuk converter driving a DC motor. This system is designed to achieve the desired speed in the DC motor using the Levenberg-Marquardt Neural Network-Based Machine Learning Algorithm. By employing this algorithm, time-domain parameters such as rise time, peak time, and settling time for achieving the desired speed are reduced compared to those obtained using traditional Proportional-Integral (PI) controllers.


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    Titel :

    Levenberg-Marquardt NN-Based Machine Learning Algorithm for DC Drive Control in Agricultural Applications


    Beteiligte:
    C, Amutha (Autor:in) / Umamaheswari, M.G. (Autor:in) / M, Dinesh (Autor:in) / K, Vinudha (Autor:in) / S S, Snekavarshini (Autor:in)


    Erscheinungsdatum :

    08.10.2024


    Format / Umfang :

    424365 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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