تلفيق داده ديناميك به كمك شبكه هاي عصبي مصنوعي

Data Reconciliation by Using Artificial Neural Networks

Artificial Neural Networks (ANNs) with advantages such as learning and estimation capabilities are widely used in various fields of chemical engineering such as process simulation and control. They are suitable for modeling, simulation, and solution of highly nonlinear problems. One of these problems is Nonlinear Dynamic Data Reconciliation. In this paper a new method, namely NetDDR, which uses ANNs, is described. NDDR of a distillation column is used to illustrate different aspects and advantages of the new method.