Control for Bioethanol Production in a Pressure Swing Adsorption Process Using an Artificial Neural Network

Control for Bioethanol Production in a Pressure Swing Adsorption Process Using an Artificial Neural Network

This paper introduces a new approach to controlling Pressure Swing Adsorption (PSA) using a neural network controller based on a Model Predictive Control (MPC) process. We use a Hammerstein–Wiener (HW) model representing the real PSA process data. Then, we design an MPC-controlled model based on the...

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Bibliographic Details
Main Authors: Moises Ramos-Martinez, Carlos Alberto Torres-Cantero, Gerardo Ortiz-Torres, Felipe D. J. Sorcia-Vázquez, Himer Avila-George, Ricardo Eliú Lozoya-Ponce, Rodolfo A. Vargas-Méndez, Erasmo M. Renteria-Vargas, Jesse Y. Rumbo-Morales
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Mathematics
Subjects:
artificial neural networks
pressure swing adsorption
model predictive control
bioethanol
Online Access:https://www.mdpi.com/2227-7390/11/18/3967

Internet

https://www.mdpi.com/2227-7390/11/18/3967

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