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Prescribed Performance Fault-Tolerant Control for Synchronization of Heterogeneous Nonlinear MASs Using Reinforcement

Donghao Liu, Zehui Mao, Bin Jiang

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    Summary
    This summary is machine-generated.

    This study introduces a new fault-tolerant control method for multiagent systems (MASs) that ensures synchronization despite actuator faults and unknown system dynamics. The approach uses reinforcement learning for robust performance and fixed-time leader state estimation.

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    Area of Science:

    • Control Systems Engineering
    • Artificial Intelligence
    • Nonlinear Systems

    Background:

    • Multiagent systems (MASs) face challenges in synchronization due to actuator faults and limited information exchange.
    • Achieving prescribed performance in MASs under uncertainty requires robust control strategies.

    Purpose of the Study:

    • To develop a novel prescribed performance synchronization control for heterogeneous nonlinear MASs with unknown actuator faults.
    • To address leader information accessibility issues using a distributed auxiliary perception system.
    • To design a data-driven fault-tolerant controller independent of system dynamics.

    Main Methods:

    • A distributed auxiliary perception system for fixed-time leader state estimation.
    • A prescribed performance fault-tolerant control (FTC) strategy.
    • A reinforcement learning (RL) algorithm for data-based controller design using off-policy data.

    Main Results:

    • The proposed method guarantees fixed-time convergence of leader state estimation errors.
    • Achieves user-defined performance specifications and fault tolerance in heterogeneous nonlinear MASs.
    • Demonstrates controller effectiveness through simulation, validating stability and prescribed synchronization.

    Conclusions:

    • The developed data-driven FTC approach ensures robust synchronization with prescribed performance for MASs under faults.
    • The method is independent of system dynamics, offering practical advantages.
    • Validated stability and performance using Lyapunov stability theorem and simulations.