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A Decentralized Designed Distributed Observer for Linear Interconnected Systems.

Shuaiting Huang, Lingying Huang, Peng Yi

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    This study introduces a distributed observer for interconnected systems, enabling subsystems to estimate the entire system state. The method ensures stable estimation error dynamics and uses local information for decentralized operation, proven effective in vehicle platooning.

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    Area of Science:

    • Control Systems Engineering
    • Networked Systems Theory
    • Distributed Computing

    Background:

    • Interconnected systems present challenges for state estimation due to complex couplings.
    • Traditional centralized observers are often impractical for large-scale distributed systems.
    • Distributed State Estimation (DSE) is crucial for monitoring and control in networked environments.

    Purpose of the Study:

    • To develop a novel distributed observer for discrete-time interconnected systems.
    • To enable individual subsystems to estimate the complete system state.
    • To establish conditions for stable estimation error and propose a decentralized design.

    Main Methods:

    • Inspired by leader-follower consensus, a distributed observer architecture is proposed.
    • Stability conditions for estimation error dynamics are derived.
    • A decentralized observer design utilizing local information and neighbor communication is presented.
    • Observability decomposition is employed for application to Linear Time-Invariant (LTI) systems.

    Main Results:

    • Necessary and sufficient conditions for the stability of the estimation error dynamics are established.
    • A decentralized observer design is achieved, relying solely on local data and inter-subsystem communication.
    • The framework is demonstrated to be applicable to DSE for LTI systems.
    • Effectiveness is validated through application to vehicle platooning scenarios.

    Conclusions:

    • The proposed distributed observer effectively addresses state estimation in interconnected systems.
    • The decentralized approach enhances practicality by leveraging local information.
    • The method provides a robust framework for distributed estimation with proven stability guarantees.