  Coalitional control is concerned with the management of multi-agent systems
where cooperation cannot be taken for granted (due to, e.g., market
competition, logistics). This paper proposes a model predictive control (MPC)
framework aimed at large-scale dynamically-coupled systems whose individual
components, possessing a limited model of the system, are controlled
independently, pursuing possibly competing objectives. The emergence of
cooperating clusters of controllers is contemplated through an autonomous
negotiation protocol, based on the characterization as a coalitional game of
the benefit derived by a broader feedback and the alignment of the individual
objectives. Specific mechanisms for the cooperative benefit redistribution that
relax the cognitive requirements of the game are employed to compensate for
possible local cost increases due to cooperation. As a result, the structure of
the overall MPC feedback can be adapted online to the degree of interaction
between different parts of the system, while satisfying the individual
interests of the agents. A wide-area control application for the power grid
with the objective of minimizing frequency deviations and undesired inter-area
power transfers is used as study case.
