We address the problem to control a population of noncooperative heterogeneous agents, each with strongly convex cost function depending on the average population state, and all sharing a convex constraint, towards a competitive aggregative equilibrium. We assume an information structure through which a central controller has access to the average population state and can broadcast control signals for steering the decentralized optimal responses of the agents. We propose a dynamic control law that, based on monotone operator theory 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: demand side management and network congestion control.
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