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Distributed generalized Nash equilibrium seeking: A singular perturbation-based approach

  • Wen-Ting Lin
  • , Guo Chen*
  • , Chaojie Li
  • , Tingwen Huang
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

In this paper, a distributed optimization algorithm is proposed for aggregative game with coupled constraints. Based on the singular perturbation system, the generalized Nash equilibrium is sought by a group of agents. By employing the average consensus method in the fast manifold, the aggregates in the object function can be estimated via simple information exchanges, as well as the aggregate of dual variables, which provides necessary information for the fully distributed algorithm design. Moreover, the exponential convergence of the proposed algorithm is explored based on the Lyapunov method, the properties of the variational inequality and the characteristic of the singular perturbation system. Application to the resource competition problem in smart grid verifies the effectiveness of the proposed algorithm. © 2021 Elsevier B.V.
Original languageEnglish
Pages (from-to)278-286
JournalNeurocomputing
Volume482
Online published26 Nov 2021
DOIs
Publication statusPublished - 14 Apr 2022
Externally publishedYes

Funding

This work is supported by the National Natural Science Foundation of China under Grant 62073344.

Research Keywords

  • Coupled constraints
  • Distributed optimization
  • Nash equilibrium
  • Smart grid

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