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Optimal Consensus Control for Continuous-Time Linear Multiagent Systems: A Dynamic Event-Triggered Approach.

Hao Zhang, Anqing Wang, Wenqiang Ji

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    Summary
    This summary is machine-generated.

    This study introduces a dynamic event-triggered method for optimal consensus in linear multiagent systems (MASs). The approach minimizes costs without needing full system information, enhancing control efficiency and performance.

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    Area of Science:

    • Control Theory
    • Networked Systems
    • Optimization

    Background:

    • Optimal consensus is crucial for coordinating multiagent systems (MASs).
    • Traditional methods often require global information, limiting practical application.
    • Event-triggered control offers potential for reduced communication and computation.

    Purpose of the Study:

    • To develop a dynamic event-triggered approach for the optimal consensus problem in general linear MASs.
    • To design a novel distributed triggering function and consensus protocol.
    • To overcome the information dependency of traditional optimal consensus methods.

    Main Methods:

    • Proposing a modified interaction-related cost function.
    • Developing a dynamic event-triggered consensus protocol with a new distributed triggering function.
    • Deriving sufficient conditions for optimality.
    • Analyzing the tradeoff between performance and event-triggered behavior.

    Main Results:

    • The proposed method minimizes the modified cost function using distributed control laws.
    • Optimal consensus gain matrices are independent of system dynamics, initial states, and network scale.
    • The approach relaxes constraints on controller design.
    • Simulation results validate the effectiveness of the designed controller.

    Conclusions:

    • The dynamic event-triggered approach effectively solves the optimal consensus problem for linear MASs.
    • The method enhances control efficiency by reducing information requirements.
    • The controller design is flexible and adaptable to various system parameters.