Industrial application of a large-scale dynamic data reconciliation strategy

In a modern chemical plant, distributed control systems provide access to a wide variety of process data that typically contain both random and gross errors. Although data reconciliation has been an often-studied topic to red uce the amount of error in measurements, applications of dynamic data recon ciliation to problems in industry are virtually nonexistent. This is becaus e standard formulations of the dynamic data reconciliation problem result i n large nonlinear programs, which are thought to be too difficult to solve in real time. With increases in computing speeds and improvements in optimi zation technology, these concerns are diminishing. This paper describes the implementation of a dynamic data reconciliation application at an ExxonMob il Chemical Company plant. The specifics of the application will be discuss ed and some solutions to the practical problems encountered in an industria l setting are presented.