An economic model predictive control framework for mechanical pulping processes

Abstract

We develop a multi-objective economic model predictive control (m-econ MPC) framework to control and optimize a nonlinear mechanical pulping (MP) process. M-econ MPC interprets economic MPC as a multi-objective optimization problem that trades off economic and set-point tracking performance. This interpretation allows us to construct a stabilizing constraint that guarantees closed-loop stability. The framework infers unmeasured states of the MP process (associated with product consistency) by using a moving horizon estimator (MHE). The MP process dynamics are described by using a nonlinear Wiener model. Examples from a two-stage high-consistency MP process are employed to demonstrate that significant improvements in economic performance are achievable.