Distributed model predictive control with one-step delay communication for large-scale systems and a case study

A distributed model predictive control (MPC) scheme with one-step delay communication is proposed for on-line optimization and control of large-scale systems in this paper. Cooperation between subsystems is achieved by exchanging information with neighbor-to-neighbor communication and by optimizing the local problem with the improved performance index in the neighborhood. A distributed MPC algorithm with one-step delay communication is developed for the situation that there is a one-step delay in the information available from its neighbors when a subsystem solves the local optimization problem. The nominal stability is employed for the whole system under the distributed MPC algorithm without the inequality constraints. Finally, the case study of the reactor-storage-separator (RSS) system is illustrated to test the practicality of the presented control algorithm. © 2014, Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg.