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Observer-Based Robust Coordinated Control of Multiagent Systems With Input Saturation.

Xiaoling Wang, Housheng Su, Michael Z Q Chen

    IEEE Transactions on Neural Networks and Learning Systems
    |April 20, 2017
    PubMed
    Summary
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    This study presents a robust control method for multiagent systems facing input limitations and disturbances. The developed observer-based protocol ensures reliable coordinated control, achieving consensus or swarm behavior in connected systems.

    Area of Science:

    • Control Systems Engineering
    • Robotics
    • Networked Systems

    Background:

    • Multiagent systems (MAS) are increasingly complex, facing challenges like input saturation, dead zones, and external disturbances.
    • Achieving robust coordinated control in such systems is crucial for reliable operation and task completion.

    Purpose of the Study:

    • To develop a robust semiglobal coordinated control protocol for multiple-input multiple-output (MIMO) multiagent systems.
    • To address limitations including input saturation, dead zones, and additive disturbances.
    • To ensure robust semiglobal consensus or swarm behavior in undirected connected MAS.

    Main Methods:

    • An observer-based coordinated control protocol was designed.
    • Combined parameterized low-and-high-gain feedback with high-gain observer design.

    Related Experiment Videos

  • Utilized mild assumptions on agents' intrinsic dynamics.

    • Main Results:

    • Demonstrated the achievement of robust semiglobal consensus or swarm behavior for undirected connected MAS.
    • Provided specific guidelines for selecting control parameters (low-gain, high-gain, observer gain).
    • Validated theoretical findings through numerical simulations.

    Conclusions:

    • The proposed observer-based protocol effectively achieves robust semiglobal coordinated control in MIMO MAS with input nonlinearities and disturbances.
    • The study offers practical guidance for parameter tuning, enhancing the applicability of the control strategy.
    • The results confirm the feasibility of robust consensus and swarm formation in complex multiagent environments.