Distributed convex optimization as a tool for solving f-consensus problems

doi:10.1016/j.automatica.2023.111087

Distributed convex optimization as a tool for solving f-consensus problems

2023-09-01

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DOI：10.1016/j.automatica.2023.111087

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For a group of networked agents, f-consensus means reaching consensus upon the value of a desired function, f, of the initial state of the individual agents. This paper shows how one can often convert a given f-consensus problem into a suitable distributed convex optimization (DCO) problem, which can be readily solved with existing DCO algorithms in the literature. A computational advantage may then accrue. Particular classes of f-consensus problems shown to be solvable with this approach include weighted power mean consensus, and kth smallest value or kth order statistic consensus (which includes max/min consensus and median consensus as special cases).& COPY; 2023 Elsevier Ltd. All rights reserved.

Keywords:

Multiagent system

Distributed optimization

f-consensus

Distributed convex optimization as a tool for solving f-consensus problems

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