  This paper addresses a class of network games played by dynamic agents using
their outputs. Unlike most existing related works, the Nash equilibrium in this
work is defined by functions of agent outputs instead of full agent states,
which allows the agents to have more general and heterogeneous dynamics and
maintain some privacy of their local states. The concerned network game is
formulated with agents modeled by uncertain linear systems subject to external
disturbances. The cost function of each agent is a linear quadratic function
depending on the outputs of its own and its neighbors in the underlying graph.
The main challenge stemming from this game formulation is that merely driving
the agent outputs to the Nash equilibrium does not guarantee the stability of
the agent dynamics. Using local output and the outputs from the neighbors of
each agent, we aim at designing game strategies that achieve output Nash
equilibrium seeking and stabilization of the closed-loop dynamics.
Particularly, when each agents knows how the actions of its neighbors affect
its cost function, a game strategy is developed for network games with digraph
topology. When each agent is also allowed to exchange part of its compensator
state, a distributed strategy can be designed for networks with connected
undirected graphs or connected digraphs.
