This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties.


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    Titel :

    Robust tracking control of space robot via neural network


    Beteiligte:
    Baomin Feng, (Autor:in) / Guangcheng Ma, (Autor:in) / Weinan Xie, (Autor:in) / Changhong Wang, (Autor:in)


    Erscheinungsdatum :

    01.01.2006


    Format / Umfang :

    1683389 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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