Advanced Process Control in the Cement and Mining Industries Based on Modular First-Principles Models

摘要

Nowadays, advanced process control techniques are most frequently used in the chemical and petrochemical industries. However, the minerals processing industry poses interesting challenges that these techniques can successfully tackle. We will first describe the formulation of model-predictive control (MPC) strategies using modular first-principles models. In real-life applications, a state estimation technique such as moving-horizon estimation (MHE) is frequently required. Combining MPC and MHE offers the possibility of sharing a common model. We propose two different modeling frameworks - linear mixedlogical dynamical (MLD) models and non-linear Modelica models. Both offer the advantage that process models can be assembled from basic units, thus making the resulting control strategies easy to understand and to modify. The second part is dedicated to applications of the abovementioned approach to the minerals processing industry.