This paper presents the fault tolerant control (FTC) of an unmanned airship with multiple vectored thrusters in the presence of model parameter uncertainties and unknown wind disturbances. A fault tolerant control based on constrained adaptive backstepping (CAB) approach, combined with a radial basis function neural network (RBFNN) approximation, is proposed for the airship with thruster faults. A wind observer is designed to estimate the bounded wind disturbances. An adaptive fault estimator is proposed to estimate the unknown actuator faults. A weighted pseudo inverse based control allocation is incorporated to reconstruct and optimize the practical control inputs of the failed airship under constraints of actuator saturation. Rigorous stability analysis shows that trajectory tracking errors of the airship position and attitude converge to the desired set through Lyapunov theory. Numerical simulations demonstrate the fault tolerant trajectory tracking capability of the proposed NN-CAB controller under the actuator faults, even in the presence of aerodynamic coefficient uncertainties, and unknown wind disturbances.


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    Title :

    Neural network adaptive backstepping fault tolerant control for unmanned airships with multi-vectored thrusters


    Contributors:


    Publication date :

    2021-09-01


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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