  We consider a system of single- or double integrator agents playing a
generalized Nash game over a network, in a partial-information scenario. We
address the generalized Nash equilibrium seeking problem by designing a
fully-distributed dynamic controller, based on continuous-time consensus and
primal-dual gradient dynamics. Our main technical contribution is to show
convergence of the closed-loop system to a variational equilibrium, under
strong monotonicity and Lipschitz continuity of the game mapping, by leveraging
monotonicity properties and stability theory for projected dynamical systems.
