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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    Title :

    Robust tracking control of space robot via neural network


    Contributors:


    Publication date :

    2006-01-01


    Size :

    1683389 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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