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    This study introduces a model-free adaptive fault-tolerant formation control (MFAFTFC) scheme for nonlinear multiagent systems (MASs). The proposed method effectively manages actuator faults and channel fading to achieve formation objectives.

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    Area of Science:

    • Control Systems Engineering
    • Robotics
    • Artificial Intelligence

    Background:

    • Multiagent systems (MASs) face challenges like actuator faults and channel fading.
    • These issues complicate nonlinear continuous-time Multiple-Input Multiple-Output (MIMO) formation control.

    Purpose of the Study:

    • To develop a model-free adaptive fault-tolerant formation control (MFAFTFC) scheme.
    • To address actuator faults and channel fading in nonlinear continuous-time MIMO MASs.

    Main Methods:

    • Utilized sampled-data full-form dynamic linearization (SD-FFDL) technology.
    • Integrated data-based formation control, Fuzzy Neural Network (FNN), and projection algorithms.
    • Provided rigorous stability analysis for the MFAFTFC scheme.

    Main Results:

    • The proposed MFAFTFC scheme successfully achieves formation control objectives.
    • Demonstrated effectiveness through simulation comparisons with Unmanned Ground Vehicles (UGVs).

    Conclusions:

    • The MFAFTFC scheme is effective for nonlinear continuous-time MIMO MASs.
    • The method robustly handles actuator faults and fading channels in formation control.