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Related Experiment Video

Updated: Apr 29, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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Adaptive Output Consensus Control for Unknown Discrete-Time Multiagent Systems With Sensor Uncertainties Under

Yuqian Lin, Yajie Ma, Bin Jiang

    IEEE Transactions on Cybernetics
    |April 27, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study addresses leader-follower output consensus (LFOC) in unknown discrete-time multiagent systems (DTMASs) with sensor uncertainties. A novel adaptive controller achieves LFOC despite stochastic communication and sensor issues.

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    Last Updated: Apr 29, 2026

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.2K

    Area of Science:

    • Control Theory
    • Systems Engineering
    • Robotics

    Background:

    • Multiagent systems (MAS) face challenges in achieving coordinated control due to uncertainties.
    • Discrete-time multiagent systems (DTMASs) require robust control strategies for reliable operation.
    • Sensor uncertainties and stochastic communication protocols (SCP) complicate consensus control.

    Purpose of the Study:

    • To develop a control strategy for leader-follower output consensus (LFOC) in DTMASs with unknown dynamics and sensor uncertainties.
    • To design an adaptive compensator to mitigate sensor uncertainties.
    • To implement a controller that operates effectively under a stochastic communication protocol (SCP).

    Main Methods:

    • An adaptive compensator was designed to estimate and counteract sensor uncertainties.
    • A unified Markov chain was constructed to model the consensus error dynamics under SCP.
    • A distributed adaptive output feedback controller was proposed for LFOC.

    Main Results:

    • The adaptive compensator successfully eliminated the effects of sensor uncertainties.
    • The proposed controller achieved LFOC for the DTMAS under SCP.
    • Simulation results validated the effectiveness of the controller in guaranteeing output consensus.

    Conclusions:

    • The developed adaptive control strategy effectively addresses LFOC in DTMASs with sensor uncertainties and SCP.
    • The approach provides a robust solution for achieving coordinated control in complex multiagent systems.
    • The findings contribute to the advancement of control theory for uncertain and stochastic systems.