Distributed MPC of constrained linear systems with time-varying terminal sets

This paper proposes a decoupling strategy for the Distributed Model Predictive Control (DMPC) for a network of dynamically-coupled linear systems. Like most DMPC approaches, the proposed approach has a terminal set and uses a Lyapunov matrix for the terminal cost in the online optimization problem for each system. Unlike them, the terminal set changes at every time step and the Lyapunov matrix is not block-diagonal. These features result in a less conservative DMPC formulation. The proposed method is easy to implement when the network is strongly connected (or when a central collector is used). Otherwise, the computations of the terminal set require the online solutions of a series of linear programming problems but can be speeded up significantly by preprocessing. Numerical examples showing these results are provided.