  We consider strongly monotone games with convex separable coupling
constraints, played by dynamical agents, in a partial-decision information
scenario. We start by designing continuous-time fully distributed feedback
controllers, based on consensus and primal-dual gradient dynamics, to seek a
generalized Nash equilibrium in networks of single-integrator agents. Our first
solution adopts a fixed gain, whose choice requires the knowledge of some
global parameters of the game. To relax this requirement, we conceive a
controller that can be tuned in a completely decentralized fashion, thanks to
the use of uncoordinated integral adaptive weights. We further introduce
algorithms specifically devised for generalized aggregative games. Finally, we
adapt all our control schemes to deal with heterogeneous multi-integrator
agents and, in turn, with nonlinear feedback-linearizable dynamical systems.
For all the proposed dynamics, we show convergence to a variational
equilibrium, by leveraging monotonicity properties and stability theory for
projected dynamical systems.
