One-layer robust MPC: a multi-model approach

FERRAMOSCA, ANTONIO; GONZÁLEZ, ALEJANDRO HERNÁN; LIMÓN, DANIEL; ODLOAK, DARCI

Cape Town

Congreso; 19th IFAC World Congress; 2014

In the process industries, the task of a model predictive controller (MPC) is to control theplant ensuring stability and constraints satisfaction, while an economic objective is fulfilled. This taskis accomplished by means of a hierarchical control structure: the economic objective is optimized byan upper level Real Time Optimizer (RTO), which choose the point the satisfies the economic criterion,among the admissible steady operation point of the plant. This point is then sent to the MPC as a setpoint.The drawback of this structure is the possible inconsistence/unreachability of this setpoint, due to thedifferent models employed by the RTO and the MPC, as well as their different time scales. In thispaper, an MPC that explicitly integrates the RTO structure into the dynamic control layer is presented.In particular, a robust MPC is proposed, which takes into account the uncertainties that arise from thedifference between nonlinear and linear models, by means of a multi-model approach.