A gradient-based strategy for the one-layer RTO+MPC controller

Abstract

In the process industries model predictive controllers (MPC) have the task of controlling the plant ensuring stability and constraints satisfaction, while an economic cost is minimized. Usually the economicobjective is optimized by an upper level Real Time Optimizer (RTO) that passes the economically optimalsetpoints to the MPC level. The drawback of this structure is the possible inconsistence/unreachabilityof those setpoints, due to the different models employed by the RTO and the MPC, as well as their dif-ferent time scales. In this paper an MPC that explicitly integrates the RTO structure into the dynamiccontrol layer is presented. To overcome the complexity of this one-layer formulation a gradient-basedapproximation is proposed, which provides a low-computational-cost suboptimal solution.