Distributed static output feedback robust model predictive control for process networks

This paper formulates a distributed static output feedback robust model predictive control for process networks to solve problems relating to unmeasured states and interconnected couplings. The initial conditions on the couplings are predicted by previous information and the boundedness of the predicted error is proved. In light of the static output feedback design conditions, the distributed static output feedback robust model predictive control is designed by transforming an infinite time optimization problem into a tractably solved one. The solvability of the optimization problem and the stability are proved to underpin the proposed approach. Simulations and an experimental case study are provided to validate the effectiveness of the proposed approach