Local learning based soft sensing methods are effective in dealing with process nonlinearities as well as time varying characteristics. In this paper, an anti-over-fitting method is proposed for appropriate online local model adaptation. The proposed method is based on the weighted sum of the predicted errors for the newest few samples, the weights of which are determined adaptively. Moreover, ...

  Abstract: In this paper, Artificial Neural Network (ANN) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. The actual input-output data of the system were measured in order to be used for system identification based on root mean square error (RMSE) minimization approach. It was shown that the designed recurrent neural network is able to pr...

Fluid catalytic cracking (FCC) process is a vital refinery process which majorly produces gasoline. In this research, a hybrid algorithm which was constituted of Adaptive Neuro-Fuzzy Inference System (ANFIS) and firefly optimization algorithm was developed to model the process and optimize the operating conditions. To conduct the research, industrial data of Abadan refinery FCC process were car...

In this paper, the Real Time Evolution algorithm (Sequeira et al., 2002) is applied to the on-line optimization of a debutanizer distillation column. A fault diagnosis system (FDS) implemented within a supervisory module is responsible for handling incidences (faults and disturbances) happening in the plant by taking the appropriate corrective actions, including the activation of the RTE system...

The current method for composition measurement of an industrial distillation column includes an offline method, which is slow, tedious and could lead to inaccurate results. Among advantages of using online composition designed are to overcome the long time delay introduced by laboratory sampling and provide better estimation, which is suitable for online monitoring purposes. This paper pres...

Debutanizer column is an important unit operation in petroleum refining industries. The design of online composition prediction by using neural network will help improve product quality monitoring in an oil refinery industry by predicting the top and bottom composition of n-butane simultaneously and accurately for the column. The single dynamic neural network model can be used and designed to o...

The debutanizer column is an important unit operation in petroleum refining industries as it is the main column to produce liquefied petroleum gas as its top product and light naphtha as its bottom product. This system is difficult to handle from a control standpoint due to its nonlinear behavior, multivariable interaction and existence of numerous constraints on both its manipulated and state ...

the main objective of this study is the modelling and optimization of an industrial hydrocracker unit (hu) by means of adaptive neuro fuzzy inference system (anfis) model. in this case, some data were collected from an industrial hydrocracker plant. inputs of an anfis include flow rate of fresh feed and recycle hydrogen, temperature of reactors, mole percentage of h2 and h2s, feed flow rate and...