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    Area of Science:

    • Control Theory
    • Networked Systems
    • Optimization

    Background:

    • Multiagent systems face challenges in achieving consensus, especially with heterogeneous agents and complex network topologies.
    • Distributed control is crucial for scalability and robustness in networked systems.
    • Optimal output consensus requires agents to agree on a common output value that minimizes a global cost function.

    Purpose of the Study:

    • To investigate the distributed optimal output consensus problem for heterogeneous linear multiagent systems.
    • To develop a novel distributed continuous-time state feedback controller for achieving optimal consensus.
    • To extend the control strategy to an observer-based output feedback setting.

    Main Methods:

    • Design of a distributed continuous-time state feedback controller.
    • Analysis of system convergence under strong connectivity and strong convexity conditions.
    • Extension of the state feedback to an observer-based output feedback controller.
    • Mathematical modeling of heterogeneous linear multiagent systems over weight-unbalanced directed networks.

    Main Results:

    • The proposed controller achieves exponential convergence of agent outputs to the optimal solution of the global cost function.
    • The control scheme is effective even for weight-unbalanced directed networks.
    • The state feedback control law is successfully extended to an observer-based output feedback setting.
    • Demonstration of the proposed control schemes' effectiveness through two illustrative examples.

    Conclusions:

    • The developed distributed control strategies effectively solve the optimal output consensus problem for heterogeneous linear multiagent systems.
    • The controller ensures convergence to the global optimum under specified network and cost function conditions.
    • The observer-based extension provides a practical solution for scenarios where states are not directly measurable.