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Utilizing vmTracking to Improve the Accuracy of Multi-Animal Pose Estimation in Rodent Social Behavior Studies
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Distributed Output Formation Optimal Tracking of Heterogeneous Linear Multiagent Systems via Distributed Time-Varying

Tingting Wang, Zhi Feng, Xiwang Dong

    IEEE Transactions on Cybernetics
    |April 10, 2026
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    Summary
    This summary is machine-generated.

    This study enables heterogeneous multiagent systems (MASs) to achieve optimal formation tracking using a novel distributed optimization algorithm. The approach generates reference trajectories, ensuring MASs reach desired formations efficiently.

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    Area of Science:

    • Control Systems Engineering
    • Robotics
    • Distributed Computing

    Background:

    • Existing formation tracking methods often rely on predetermined paths.
    • Heterogeneous multiagent systems (MASs) present unique challenges in coordinated control.
    • Achieving optimal tracking while maintaining formation is a complex control problem.

    Purpose of the Study:

    • To develop a distributed control strategy for optimal output formation tracking in heterogeneous multiagent systems (MASs).
    • To enable MASs to track an optimal reference trajectory generated via distributed optimization, rather than relying on prespecified trajectories.
    • To ensure convergence in both consensus and optimality under inequality constraints.

    Main Methods:

    • A distributed time-varying optimization algorithm was designed to generate optimal reference trajectories.
    • A distributed output formation optimal tracking control protocol was developed, integrating the trajectory generator.
    • Lyapunov stability analysis was employed to rigorously prove the convergence of the control algorithm.

    Main Results:

    • The proposed distributed optimization algorithm achieves fixed-time convergence in consensus and asymptotic convergence in optimality, handling inequality constraints.
    • The integrated control protocol ensures that heterogeneous MASs achieve desired formations while tracking the optimal reference trajectory.
    • Simulation examples validated the effectiveness and theoretical soundness of the proposed distributed control strategy.

    Conclusions:

    • The developed distributed control framework successfully addresses optimal output formation tracking for heterogeneous MASs.
    • The novel approach offers a more flexible and optimal solution compared to methods using prespecified trajectories.
    • The findings contribute to advancements in coordinated control and optimization for multiagent systems.