Evaluation of Nonlinear Inferential Models to Estimate the Products Quality of Industrial Distillation Process

The problem of improvement of existing approaches for evaluation of inferential models used in the advanced process control systems is considered. The method of finding the identifiability index limit, based on the physically-chemical essence of the industrial distillation process, for the inferential models containing nonlinear transformations of measured inputs is given. The problem of handling the narrow variability range of key inputs in the training sample is considered. The paper contains the example of evaluating the inferential models based on the proposed method applied to the nonlinear industrial distillation plant.