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    Area of Science:

    • Control Theory
    • Robotics
    • Distributed Systems

    Background:

    • Distributed Average Tracking (DAT) is typically used for estimation.
    • Dynamic Region-Following Formation Control (DRFFC) requires agents to follow a moving region.
    • Existing DRFFC methods often need regular region shapes and have limitations.

    Purpose of the Study:

    • To establish a connection between DAT and DRFFC.
    • To develop robust DAT algorithms for linear multiagent systems.
    • To apply DAT for solving the DRFFC problem.

    Main Methods:

    • Proposed a fixed-gain DAT algorithm robust to initialization errors.
    • Developed an adaptive control gain DAT algorithm removing upper bound restrictions.
    • Derived DRFFC algorithms from the DAT algorithms for various linear dynamics.

    Main Results:

    • Achieved zero tracking error for a broad range of reference signals using DAT.
    • Demonstrated DAT algorithm applicability to DRFFC.
    • Developed DRFFC algorithms that do not require regular region shapes.
    • Generated richer formation behaviors compared to existing methods.

    Conclusions:

    • DAT algorithms can be effectively used for distributed control, specifically DRFFC.
    • The proposed DAT-based DRFFC algorithms offer greater flexibility and richer formation capabilities.
    • Validated the approach through numerical examples for single-integrator, double-integrator, and higher-order linear dynamics.