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    Area of Science:

    • Control Systems Engineering
    • Robotics
    • Artificial Intelligence (Fuzzy Logic)

    Background:

    • Nonlinear multiagent systems (NMASs) often face challenges with unknown dynamics and intermittent actuator faults.
    • Existing fault-tolerant control (FTC) methods may not adequately address these combined complexities in distributed systems.
    • Adaptive control and fuzzy logic systems (FLSs) offer potential solutions for handling uncertainties and faults.

    Purpose of the Study:

    • To develop a distributed adaptive fuzzy consensus fault-tolerant control (FTC) strategy for NMASs with intermittent actuator faults.
    • To address unknown nonlinear dynamics using fuzzy-logic systems (FLSs) approximation.
    • To ensure robust system performance and stability under directed communication topologies.

    Main Methods:

    • Approximation of unknown nonlinear dynamics using fuzzy-logic systems (FLSs).
    • Design of distributed virtual controllers and parameter adaptive laws using adaptive backstepping and bounded estimation algorithms.
    • Co-design of novel adaptive fuzzy consensus fault-tolerant controllers to compensate for intermittent actuator faults.
    • Stability analysis based on Lyapunov theory to guarantee asymptotic convergence of tracking errors.

    Main Results:

    • The proposed adaptive fuzzy consensus FTC scheme effectively compensates for intermittent actuator faults in NMASs.
    • Tracking errors of the closed-loop system converge asymptotically to zero under directed communication topologies.
    • The control strategy demonstrates practicability and effectiveness when applied to one-link robotic manipulator systems.

    Conclusions:

    • The developed distributed adaptive fuzzy consensus FTC approach provides a robust solution for NMASs with intermittent actuator faults and unknown dynamics.
    • The integration of fuzzy logic, adaptive backstepping, and bounded estimation enables effective fault compensation and stability.
    • The successful validation on robotic manipulators confirms the proposed scheme's real-world applicability.