Soft sensor for Multicomponent distillation Column using Neural Network and Genetic Algorithm based Techniques

The time to measure and maintain distillate quality in the presence of disturbances is the main objective of distillation process. In this paper a novel approach based on hybrid soft computing technique is proposed to estimate the product composition of a multicomponent distillation column on the basis of simulated time series data. A Genetic Algorithm (GA) based Neural Network is constructed as a soft sensor for the estimation of composition. The results are compared with Artificial Neural Network (ANN) based soft sensor. From the detailed dynamic simulation results, it is found that the proposed GA based Neural Network estimator works better than ANN based soft sensor. The performance of estimator is evaluated in the presence of noise in the input.