Distributed Economic MPC With Separable Control Contraction Metrics

In this letter, a flexible and scalable distributed economic model predictive control scheme is proposed for large-scale networked systems consisting of nodes with local self-interest economic objectives but a shared responsibility for stability of the interconnected network. In this letter, subsystems are controlled to track reference trajectories while optimizing their own economic costs during the transitions. A reference-independent stability constraint is introduced using a sum-separable control contraction metric. The proposed control design approach is thereby independent of both reference trajectories and the economic cost functions and as such suitable for flexible manufacturing. We observe that self-interested distributed optimization with shared responsibility for stability results in the same general problem formulation as network utility maximization, and make use of the alternating direction method of multipliers to coordinate the optimization. The proposed approach is illustrated with an example of distributed control of a network with 120 nodes, each of which is a three-state nonlinear system.