Steady-state target calculation integrating economic optimization for constrained model predictive control

Abstract

Real-time optimization (RTO) in cascade model predictive control (MPC) is a classic two-layer architecture for economic optimization and dynamic control. The two-layer architecture is always integrated with steady-state target calculation (SSTC) to guarantee the feasibility of the control target. In this paper, we present a modified SSTC algorithm to recalculate the steady-state point for MPC when the optimal point calculated by RTO is no longer attainable. The proposed algorithm takes economic performance into account and retains the feasibility of solutions. Based on a classic SSTC formulation, ours has a new objective function with two terms, one for optimizing economic performance and the other for ensuring the feasibility. Moreover, the objective function of the proposed SSTC is rearranged, and the SSTC problem is formulated by quadratic programming, which can be solved in an instant for real applications. Furthermore, we provide a detailed 4-in-4-out model of the Fischer esterification reaction, which is similar to the benchmark continuous stirred tank reactor (CSTR) model, to demonstrate the effectiveness of our SSTC algorithm. The proposed algorithm is able to improve economic performances, whether a convex or non-convex economic cost function is concerned.