Cooperative distributed model predictive control of multiple coupled linear systems

This study presents a cooperative distributed model predictive control (CDMPC) algorithm for a team of linear subsystems with the coupled cost and coupled constraints. At each sampling time, all the subsystems are permitted to synchronously optimise. An improved compatibility constraint, which plays an important to ensure the stability, is constructed to ensure that the actual state trajectory of each subsystem does not deviate too much from its assumed one. Moreover, a positive invariant terminal set and an associated terminal cost (a local control-Lyapunov function) are designed in the distributed manner. By applying the proposed algorithm, the recursive feasibility with respect to both local and coupled constraints and the closed-loop stability of the whole system are ensured. In final, the numerical results of the comparisons between the CDMPC algorithm and the centralised model predictive control are given to show the effectiveness of the proposed algorithm.