Highlights Attitude information converges to the equilibrium state with high precision. Explicit bounds of attitude information and estimation errors are obtained. Less conservative and easily extendable to a second-order system with input MRCs.

    Abstract This paper studies the problem of attitude stabilization for a rigid spacecraft subject to external disturbances, time-varying inertia uncertainties, and input magnitude and rate constraints (MRCs). By analyzing the influence of inertia uncertainties, the reconstruction of lumped disturbances is accomplished to facilitate the controller design. Then, a disturbance observer is designed, based on which, a simple state feedback control strategy including estimation of lumped disturbances is proposed. By choosing new state variables using attitude information and estimation errors, an augmented plant is constructed. Using standard Lyapunov stability analysis, which shows that all states are uniformly ultimately bounded, sufficient conditions for the existence of the disturbance observer and controller are given based on linear matrix inequalities (LMIs). It is worth pointing out that the observer and controller gains are obtained simultaneously. It is shown that the control scheme developed is not only robust against external disturbances and unknown time-varying inertia uncertainties, but also able to steer the attitude control performance and estimation errors of lumped disturbances. Numerical simulations are performed to demonstrate the effectiveness of the proposed control strategy.


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    Titel :

    Disturbance observer-based attitude stabilization for rigid spacecraft with input MRCs


    Beteiligte:
    Shi, Keke (Autor:in) / Liu, Chuang (Autor:in) / Sun, Zhaowei (Autor:in) / Yue, Xiaokui (Autor:in)

    Erschienen in:

    Advances in Space Research ; 66 , 3 ; 689-701


    Erscheinungsdatum :

    2020-04-14


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch