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    This study presents an adaptive control method for multiagent systems with unknown dynamics and delays. The approach ensures accurate tracking and system stability, simplifying controller design.

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    Area of Science:

    • Control Theory
    • Systems Engineering
    • Robotics

    Background:

    • Complex heterogeneous multiagent systems often face challenges with unknown time-varying control directions (CDs) and input delays (UTVDs).
    • Existing control strategies may struggle with these uncertainties, leading to performance degradation or instability.

    Purpose of the Study:

    • To develop an event-triggered consensus tracking control strategy for multiagent systems with fully unknown CDs, UTVDs, and functions.
    • To ensure predefined transient and steady-state performance criteria for tracking errors.

    Main Methods:

    • An auxiliary system was designed to generate a compensation signal for mitigating UTVDs.
    • A novel adaptive proportional-integral (PI) control approach was developed using backstepping and Nussbaum functions.
    • An event-triggered mechanism was employed to reduce communication and computation load.

    Main Results:

    • The proposed control strategy guarantees asymptotic tracking and global boundedness of all signals within the closed-loop system.
    • The tracking error meets predefined transient and steady-state performance criteria.
    • The controller design is simplified and control performance is enhanced without prior knowledge of unknown system functions.

    Conclusions:

    • The developed event-triggered adaptive PI control approach effectively addresses consensus tracking in complex multiagent systems with significant uncertainties.
    • The method offers a practical solution with improved performance and reduced design complexity.
    • Simulation results confirm the efficacy and validity of the proposed control strategy.