Modifier Adaptation with Quadratic Approximation with Distributed Estimations of the Modifiers Applied to the MDI-Production Process

The energy and resource efficient operation of continuously operated large-scale chemical plants is an important factor in the transition towards a sustainable and green process industry. In this work, the operation of the heat exchangers in the diphenylmethane diisocyanate (MDI) process is optimized to reduce fouling and thereby increase their energy efficiency. Real-time optimization (RTO) using Modifier Adaptation With Quadratic Approximation (MAWQA) is applied to cope with plant–model mismatch. It is combined with distributed estimation of the modifiers while retaining a centralized optimization to ensure rapid convergence. It reduces the data points needed for their computation and enables application to large-scale processes. The plant model that is used in the optimization is a surrogate of an available detailed flow-sheet simulator model. The algorithm is demonstrated first for a small problem and then applied to the operator training simulator (OTS) of the MDI process in several operation scenarios. Compared to previous work, the algorithm converges to the optimal operating conditions in fewer iterations.