Continuous-time fully distributed generalized Nash equilibrium seeking for multi-integrator agents

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