摘要：AbstractIn this work, the application of a reliable iterative real-time optimization (RTO) scheme to a continuously operated transition metal complex catalyzed process for the hy-droformylation of 1-dodecene is presented. The aim of the proposed scheme is to ensure optimal operation despite the presence of model uncertainties and measurement errors. Iterative optimization using Modifier Adaptation with Quadratic Approximation (MAWQA) is applied. Furthermore, additional modules for steady-state identification (SSI) and robust data reconciliation (DR) were designed and implemented. The proposed scheme was commissioned in a real miniplant, and a significantly improved performance in comparison to the optimal operating point that was obtained from the nominal process model was achieved.
