This article presents a fuzzy adaptive tracking control algorithm for hypersonic flight vehicles with input quantization and faults. Different from the usual stabilization results, we present a method to achieve asymptotic tracking with predefined-time performance. An error transformation is established and a modified Lyapunov function (MLF) is constructed. The predefined-time asymptotic tracking control goal can be achieved by simply guaranteeing the boundness of the proposed MLF which is related to the transformed tracking errors. The proposed control strategy has three advantages. First, the predefined-time tracking performance can be ensured even when the initial tracking conditions are completely unknown. Second, no compensation is required for the fuzzy reconstruction errors to achieve accurate tracking control such that the control design is significantly simplified. Third, the derived controller is fault-tolerant, and since the system is controlled by quantized signals, the communication burden can be considerably reduced. Theoretical proof and numerical simulation are presented to demonstrate the effectiveness of the proposed control algorithm.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Predefined-Time Asymptotic Tracking Control for Hypersonic Flight Vehicles With Input Quantization and Faults


    Beteiligte:
    Li, Yajun (Autor:in) / Liang, Shuai (Autor:in) / Xu, Bin (Autor:in) / Hou, Mingshan (Autor:in)


    Erscheinungsdatum :

    01.10.2021


    Format / Umfang :

    1815311 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Predefined-Time Fault Tolerant Control for Hypersonic Vehicles Under Actuator Faults

    Chen, Fangzheng / Hu, Qinglei / Han, Tuo | Springer Verlag | 2025


    Adaptive Control for Hypersonic Vehicles With Time-Varying Faults

    Qinglei Hu / Chenliang Wang / Yun Li et al. | IEEE | 2018