An efficient cooperative-distributed model predictive controller with stability and feasibility guarantees for constrained linear systems

Abstract

This paper proposes a quadratic programming based cooperative-distributed model predictive control strategy, with stability and feasibility guarantees. Its feasibility is achieved by considering slacked terminal constraints of the optimization problem without the assessment of an invariant terminal set. The stability proof uses Lyapunov arguments and is carried out by properly setting the move suppression matrix elements for each agent. A case study involving a process system composed of two CSTR in series with a flash vessel illustrates the effectiveness of the proposed method, especially in a scenario that limits the information exchanged as well as imposes a short time interval for communication among the agents.