On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR

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 and specified variance were added to simulated results by a random number generator. the generated data are transferred on-line to a developed data reconciliation software. the software performs nddr on received data using ekf method. comparison of data reconciliation results with simulated measurements and true values demonstrates a high reduction in measurement errors, while benefits high speed data reconciliation process.