Distributed gradient descent method with edge‐based event‐driven communication for non‐convex optimization

Autor: T. Adachi, N. Hayashi, S. Takai
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IET Control Theory & Applications, Vol 15, Iss 12, Pp 1588-1598 (2021)
Druh dokumentu: article
ISSN: 1751-8652
1751-8644
DOI: 10.1049/cth2.12127
Popis: Abstract This paper considers an event‐driven distributed non‐convex optimization algorithm for a multi‐agent system, where each agent has a non‐convex cost function. The goal of the multi‐agent system is to minimize the global objective function, which is the sum of these local cost functions, in a distributed manner. To this end, each agent updates the own state by a consensus‐based gradient descent algorithm. The local information exchange among neighbor agents is carried out with an event‐triggered scheme to achieve consensus with less inter‐agent communication. Convergence to a critical point of the objective function and the validity of the proposed algorithm in numerical examples are shown.
Databáze: Directory of Open Access Journals
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