extended kalman filtering (ekf) is a nonlinear dynamic data reconciliation (nddr) method. one of its main advantages is its suitability for on-line applications. this paper presents an on-line nddr method using ekf. it is implemented for two case studies, temperature measurements of a distillation column and concentration measurements of a cstr. in each time step, random numbers with zero mean ...

Extended Kalman Filtering (EKF) is a nonlinear dynamic data reconciliation (NDDR) method. One of its main advantages is its suitability for on-line applications. This paper presents an on-line NDDR method using EKF. It is implemented for two case studies, temperature measurements of a distillation column and concentration measurements of a CSTR. In each time step, random numbers with zero m...

The technique of dynamic data reconciliation has been previously studied in the literature and shown to be an effective tool to better estimate the true values of process variables by using information from both measured values and process models. Real-time implementation of dynamic data reconciliation involves solving complex optimization problem, leading to large computation time. This paper ...

Although reconciliation of steady-state process data is routinely applied in industrial practice, the theoretical understanding of the problem and its adequate formulation in a dynamic setting is still not mature. Existing formulation approaches are based on stochastic lters, deterministic observers or mathematical programming techniques. In this contribution, we suggest a general problem formu...

Data reconciliation is a well-known method in on-line process control engineering aimed at estimating the true values of corrupted measurements under constraints. An adaptive nonlinear dynamic data reconciliation (ANDDR) method is proposed that includes the application to processes with an unknown statistical model. ANDDR enables gross error detection (GED) as well. Finally, a novel smart track...

This paper describes nonlinear methods in model building, dynamic data reconciliation, and dynamic optimization that are inspired by researchers and motivated by industrial applications. A new formulation of the l1-norm objective with a dead-band for estimation and control is presented. The dead-band in the objective is desirable for noise rejection, minimizing unnecessary parameter adjustments...

One of main thrusts of modern plant operation is to improve the quality of online information in distributed control system (DCS). Accurate information about the current state of a process is paramount for plant monitoring and control. Unfortunately, process measurements are often corrupted by measurement noise. The presence of measurement noise not only prevents plant operators from identifyin...