This work presents the development of an intelligent nonlinear sliding mode control strategy to control the motion of a quadrotor, subjected to bounded external disturbances and parametric uncertainties. As opposed to the conventional sliding manifolds, the proposed algorithm utilises a terminal sliding manifold for ensuring that the tracking error converges to its steady state value in finite time. In addition, alongside the nonlinear sliding manifold, a power rate reaching law is used to attenuate chattering. The controller gains are tuned using the principle of gradient-descent so as to mitigate the effect of external disturbances as well as parametric uncertainties in the system such that the overall control effort is minimized. The overall stability of the system as well as the expression for convergence time are analysed and obtained using the Lyapunov’s stability theory. Numerical simulations are used to demonstrate the efficacy of the proposed controller as opposed to the neural network based classical sliding mode controller. In addition, simulations are presented to establish the significance of the gain tuning approach. The presented approach is also validated in in Real-time using the DJI Matrice 100 in outdoor environment.


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    Titel :

    Trajectory Tracking Control of a Quadrotor UAV using an Auto-tuning Robust Sliding Mode Controller


    Beteiligte:


    Erscheinungsdatum :

    21.06.2022


    Format / Umfang :

    2770595 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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