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Updated: Nov 28, 2025

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Planar Affine Formation Stabilization via Parameter Estimations.

Qingkai Yang, Hao Fang, Ming Cao

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    This study addresses affine formation stabilization for multiagent systems where only one leader agent knows the target formation parameters. A novel control scheme enables two leader agents to access these parameters, ensuring unique formation stabilization.

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    Area of Science:

    • Robotics
    • Control Theory
    • Distributed Systems

    Background:

    • Multiagent systems require coordinated behavior for tasks like surveillance and exploration.
    • Stabilizing affine formations is challenging due to limited information sharing among agents.
    • Existing methods struggle with decentralized control and unknown formation parameters.

    Purpose of the Study:

    • To develop a control strategy for affine formation stabilization in multiagent systems.
    • To address the challenge of limited information access to target formation parameters (scaling, rotation).
    • To enable multiple leader agents to estimate and utilize formation parameters.

    Main Methods:

    • Proposing a class of estimators for two leader agents to gain access to formation parameters.
    • Designing an integrated control scheme for unique stabilization of the target formation.
    • Utilizing the cyclic-small-gain theorem to ensure closed-loop system stability.

    Main Results:

    • The proposed estimators successfully allow two leader agents to access formation parameters.
    • The integrated control scheme achieves unique affine formation stabilization.
    • The cyclic-small-gain theorem provides sufficient conditions for system stability.

    Conclusions:

    • The developed control strategy effectively stabilizes affine formations in multiagent systems with limited information.
    • The approach enhances coordination and robustness in decentralized robotic systems.
    • Experimental validation confirms the practical applicability of the proposed method.