Integration of RTO with MPC through the gradient of a convex function

Predictive controllers are usually implemented as part of a hierarchical structure of the process operation where the Real Time Optimization (RTO) and the Model Predictive Control (MPC) are executed in separated layers. Here, it is proposed to use the gradient of a convex function that links the optimizing targets to the MPC controller. The convex function is a nu+1 dimensional paraboloid of the process inputs, with the minimum corresponding to the input targets resulting from the RTO routine. For this MPC controller, the infinite prediction horizon and terminal state constraint are considered, and it operates according to the zone control strategy. Simulation results of a linear system are provided.