Optimal Output Consensus of Heterogeneous Linear Multiagent Systems Over Weight-Unbalanced Directed Networks

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.