In this paper, a fault tolerant control (FTC) scheme, which is based on backstepping and neural network (NN) methodology, is proposed for a general class of nonlinear systems with known structure and unknown faults. Firstly, the linearly parameterized radial basis function (RBF) NNs are employed to approximate unknown system faults, and the network weights are adapted using adaptive on-line parameter-learning algorithms. Then an adaptive backstepping based FTC is designed to compensate for the effect of system faults. The asymptotical stability of the closed-loop system and uniform boundedness of the state tracking errors are proved according to Lyapunov theory. Finally, the designed strategy is applied to near space vehicle (NSV) attitude dynamics, and simulation results are presented to demonstrate the effectiveness of the proposed approach.


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    Titel :

    Fault Tolerant Control for a Class of Nonlinear Systems with Application to Near Space Vehicle


    Beteiligte:
    Xu, Yufei (Autor:in) / Jiang, Bin (Autor:in) / Tao, Gang (Autor:in) / Gao, Zhifeng (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2011


    Format / Umfang :

    18 Seiten, 23 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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