This work addresses the application of the Robust Infinite Horizon Model Predictive Control (RIHMPC) to a heat integrated propylene distillation system at a Petrobras refinery. The approach proposed here is tested on the rigorous dynamic simulation software (Dynsim (R)) that reproduces the system as a virtual plant and is able to communicate with the MPC algorithms developed in Matlab, through an Open Platform Communication (OPC) interface. The controller is based on a minimal order state-space model that is equivalent to the system step response and considers the zone control of the outputs and optimizing targets for the inputs. The optimizing targets are obtained through the steady-state economic optimization using the real-time optimization package (ROMeo (R) 1). The proposed integration approach provides convergence and stability to the closed-loop system. The propylene distillation system is simulated with the proposed control and optimization strategies and the results show that, from the economic performance and robustness viewpoint, for this particular system, the proposed robust MPC is significantly better than the nominal IHMPC based on a single linear model obtained at the most probable operating point.