  We address the problem to control a population of noncooperative
heterogeneous agents, each with convex cost function depending on the average
population state, and all sharing a convex constraint, towards an aggregative
equilibrium. We assume an information structure through which a central
coordinator has access to the average population state and can broadcast
control signals for steering the decentralized optimal responses of the agents.
We design a dynamic control law that, based on operator theoretic arguments,
ensures global convergence to an equilibrium independently on the problem data,
that are the cost functions and the constraints, local and global, of the
agents. We illustrate the proposed method in two application domains: network
congestion control and demand side management.
