Distributed robust adaptive equilibrium computation for generalized convex games

Minghui Zhu, Emilio Frazzoli

    Research output: Contribution to journalArticlepeer-review

    61 Scopus citations

    Abstract

    This paper considers a class of generalized convex games where each player is associated with a convex objective function, a convex inequality constraint and a convex constraint set. The players aim to compute a Nash equilibrium through communicating with neighboring players. The particular challenge we consider is that the component functions are unknown a priori to associated players. We study two distributed computation algorithms and analyze their convergence properties in the presence of data transmission delays and dynamic changes of network topologies. The algorithm performance is verified through demand response on the IEEE 30-bus Test System. Our technical tools integrate convex analysis, variational inequalities and simultaneous perturbation stochastic approximation.

    Original languageEnglish (US)
    Pages (from-to)82-91
    Number of pages10
    JournalAutomatica
    Volume63
    DOIs
    StatePublished - Jan 1 2016

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Electrical and Electronic Engineering

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