Highlights The performance of tracking trajectory while keeping base stable is achieved. A state-spaced representation is developed to simplify the backstepping process. An ESO with two extended state variables depicting disturbances is developed. An RBF neural network is established to compensate dynamic uncertainties.

    Abstract In this paper, an extended-state-observer-based adaptive controller is proposed for flexible-joint space manipulators (FJSM) to accurately track trajectories while stabilizing bases in the presence of dynamic uncertainties and joint stiffness uncertainties. The dynamic model of a FJSM is established, and its state-spaced representation is obtained by introducing an error vector and a sliding mode surface vector as state variables. Besides, an extended state observer (ESO) is designed to guarantee the precise estimation of the manipulator’s velocity states as well as the joint stiffness uncertainties. Based on the ESO and the state-spaced representation, an adaptive controller is generated by implementing backstepping method, where the dynamic uncertainties are compensated by a Radial Basis Function neural network (RBFNN) and the joint stiffness uncertainties are eliminated by the estimation of the ESO. The stabilities of the ESO-based adaptive controller are validated by Lyapunov theory. Several numerical simulations were conducted, and the simulation results verifies the effectiveness of the proposed controller.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Extended-state-observer-based adaptive control of flexible-joint space manipulators with system uncertainties


    Beteiligte:
    Zhan, Bowen (Autor:in) / Jin, Minghe (Autor:in) / Liu, Jian (Autor:in)

    Erschienen in:

    Advances in Space Research ; 69 , 8 ; 3088-3102


    Erscheinungsdatum :

    2022-01-14


    Format / Umfang :

    15 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch