Distributed model predictive control for constrained linear systems

We address the distributed model predictive control (MPC) for a set of linear local systems with decoupled dynamics and a coupled global cost function. By the decomposition of the global cost function, the distributed control problem is converted to the MPC for each local system associated with a cost involving neighboring system states and inputs. For each local controller, the infinite horizon control moves are parameterized as N free control moves followed by a single state feedback law. An interacting compatibility condition is derived, disassembled and incorporated into the design of each local control so as to achieve the stability of the global closed-loop system. Each local system exchanges with its neighbors the current states and the previous optimal control strategies. The global closed-loop system is shown to be exponentially stable provided that all the local optimizers are feasible at the initial time. Copyright (C) 2009 John Wiley & Sons, Ltd.