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Summary

This summary is machine-generated.

This study introduces a new distributed protocol for multiagent systems to optimize performance while preserving network connectivity. It ensures reliable communication and state agreement, even with limited sensing or communication ranges and unexpected disturbances.

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Area of Science:

Control Systems Engineering
Distributed Computing
Network Science

Background:

Cooperative interactions in multiagent systems require preserved network connectivity for effective information exchange.
Limited sensing and communication ranges pose challenges to maintaining network connectivity by default.
Unexpected obstacles and noise can disrupt system performance and communication links.

Purpose of the Study:

To develop a distributed optimization protocol for multiagent systems that guarantees network connectivity preservation.
To achieve state agreement in finite time while optimizing the sum of local functions.
To address scenarios with unavailable initial states and ensure consensus within a prescribed finite time.

Main Methods:

Design of generalized potentials incorporating discontinuities to handle obstacles and noise.
Development of a novel distributed protocol based on these potentials.
Application of nonsmooth analysis tools to analyze the discontinuous protocol's performance.
Further development of a protocol for scenarios lacking initial state information.

Main Results:

Formal guarantee of network connectivity preservation over time.
Realization of state agreement in finite time for distributed optimization.
Successful optimization of the sum of local functions under connectivity constraints.
Demonstrated effectiveness of the proposed protocols through illustrative examples, including scenarios with unknown initial states.

Conclusions:

The proposed distributed protocols effectively achieve multiagent system optimization while ensuring network connectivity.
The methods provide robust solutions for state agreement and consensus, even in the presence of communication limitations and uncertainties.
The work offers practical solutions for real-world distributed systems requiring reliable and connected operation.