Design and Optimization of a Filter Based on Artificial Neural Network Applied to a Distillation Column

Abstract

This paper discusses the design and application of a filter based on an Artificial Neural Network (ANN) in a chemical engineering process. The design of a filter consists of adapting the algorithms that make up the filter to the process to be filtered. Taking into account that the ANN is able to model almost every type of chemical process, the design and application of a filter based on ANN was studied. In this work, every ANN used was based on Multilayer Perceptron (MLP). Bearing in mind that ANN should reproduce the process as accurately as possible, an optimisation of the ANN (training function and parameters) was carried out. A mathematical model of a reflux in the upper part of a distillation column was used to test the ANN filter. The ANN is able to filter noisy signals with a mean prediction error less than 2.5•10-3 %.