Output consensus for interconnected systems via the internal model principle and a model predictive control based strategy

Interconnected systems are commonly found in process networks. In this paper, an output consensus framework is proposed for a class of continuous interconnected linear heterogeneous systems subject to constraints. A distributed output consensus control strategy is developed by combining the internal model principle (IMP) with model predictive control (MPC). A distributed iterative algorithm is designed to solve the IMP conditions for interconnected systems. The IMP based control plays two main roles: On the one hand, it helps to deal with the interconnection effects existing between the subsystems; on the other hand, it drives the subsystems to track the reference dynamics in order to achieve output consensus. The MPC determines an optimized control gain while being able to handle constraints. Simulation examples and experimental trials are presented to validate the effectiveness and superiority of the proposed method.