Neural Network-Based Identification of a PSA Process for Production and Purification of Bioethanol

The pressure swing adsorption (PSA) process, is a novel method for the purification and production of bioethanol. A highly non-linear rigorous model implemented to simulate cyclic dynamics PSA, achieving purity 99% wt ethanol, which meets international standards be used as fuel. contribution this work focuses on obtaining an identified capable capturing important PSA process (with fit above 90%) controller design purposes, since it very complicated control in nonlinear models that are represented with partial differential equations (PDE). For proof concept, comparison between Hammersetein-Wienner Artificial Neural-Networks showed relevance proposed method, using same input output signals. Both capture model.