A hierarchical MPC scheme for coordination of independent systems with shared resources and plug-and-play capabilities

This paper describes a hierarchical control scheme for the coordination of independent, asymptotically stable, and square systems with joint input and output constraints. At the higher layer of the control structure, a centralized model predictive control (MPC) problem is solved at a slow rate based on a reduced order model of the overall system to fulfill the global output request under shared resources. At the lower layer, fast MPC controllers are designed for each subsystem to remove the effects of the model mismatch introduced at the higher layer, satisfy local constraints and optimize the individual performance. The proposed algorithm allows to dynamically modify the control configuration according to plug-and-play operations. Theoretical results of feasibility and convergence are proven and a simulation study is reported to witness the potentialities of the method.