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Main Authors: Hall, Sophie, Bemporad, Alberto
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2512.05505
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author Hall, Sophie
Bemporad, Alberto
author_facet Hall, Sophie
Bemporad, Alberto
contents We present a method to compute explicit solutions of parametric Generalized Nash Equilibrium (GNE) problems with convex quadratic cost functions and linear coupling and local constraints. Assuming the parameters only enter the linear terms of the cost functions and constraint right-hand sides, we provide the exact multiparametric solution of the GNE problem. Such a solution enables (i) minimal real-time computation, (ii) inherent interpretability, explainability, and exact enumeration of all multiple equilibria, (iii) determine desired GNE solution types in the case of infinitely-many equilibria, and (iv) zero-shot updates of the GNE solution due to changes of constraint right-hand sides and/or linear costs. In line with explicit Model Predictive Control (MPC) approaches, we apply our method to solve game-theoretic MPC (Receding Horizon Games) explicitly, comparing performance against centralized solvers in a battery charging game and in a toy two-mass spring system control problem. A Python implementation of the algorithms presented in this paper is available on https://github.com/bemporad/nash_mpqp.
format Preprint
id arxiv_https___arxiv_org_abs_2512_05505
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Solving Multiparametric Generalized Nash Equilibrium Problems and Explicit Game-Theoretic Model Predictive Control
Hall, Sophie
Bemporad, Alberto
Systems and Control
We present a method to compute explicit solutions of parametric Generalized Nash Equilibrium (GNE) problems with convex quadratic cost functions and linear coupling and local constraints. Assuming the parameters only enter the linear terms of the cost functions and constraint right-hand sides, we provide the exact multiparametric solution of the GNE problem. Such a solution enables (i) minimal real-time computation, (ii) inherent interpretability, explainability, and exact enumeration of all multiple equilibria, (iii) determine desired GNE solution types in the case of infinitely-many equilibria, and (iv) zero-shot updates of the GNE solution due to changes of constraint right-hand sides and/or linear costs. In line with explicit Model Predictive Control (MPC) approaches, we apply our method to solve game-theoretic MPC (Receding Horizon Games) explicitly, comparing performance against centralized solvers in a battery charging game and in a toy two-mass spring system control problem. A Python implementation of the algorithms presented in this paper is available on https://github.com/bemporad/nash_mpqp.
title Solving Multiparametric Generalized Nash Equilibrium Problems and Explicit Game-Theoretic Model Predictive Control
topic Systems and Control
url https://arxiv.org/abs/2512.05505