This paper is concerned with the fault-tolerant cooperative control (FTCC) problem of multiple unmanned aerial vehicles (multi-UAVs) in the communication network. By exploiting neural network (NN) to approximate the nonlinear terms existing in the highly nonlinear multi-UAVs system, a distributed neural adaptive control scheme is proposed when only a subset of follower UAVs has access to the leader UAV’s states. To solve the problem of “explosion of complexity” in traditional backstepping architecture and reduce the number of online updating parameters of NN, dynamic surface control (DSC) and minimal learning parameter techniques are employed to reduce the computational complexity. Furthermore, by combining graph theory and Lyapunov approach, it is proved that velocities and altitudes of all follower UAVs can track the velocity and altitude of the leader UAV. Finally, simulation results are presented to verify the effectiveness of the proposed control scheme.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fault-Tolerant Adaptive Neural Control of Multi-UAVs Against Actuator Faults


    Beteiligte:
    Yu, Ziquan (Autor:in) / Zhang, Youmin (Autor:in) / Qu, Yaohong (Autor:in) / Su, Chun-Yi (Autor:in) / Zhang, Yintao (Autor:in) / Xing, Zhewen (Autor:in)


    Erscheinungsdatum :

    01.06.2019


    Format / Umfang :

    447762 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Adaptive Fault-Tolerant Formation Control for Multiple UAVs Under Unknown Actuator Faults

    Wang, Gen / Liu, Zhong / Yang, Kaiwen et al. | Springer Verlag | 2024





    Fault tolerant cooperative control of multiple UAVs-UGVs under actuator faults

    Kamel, Mohamed A. / Ghamry, Khaled A. / Zhang, Youmin | IEEE | 2015