Abstract
Distillation is one of the most studied processes in the control literature because of its importance as a separation process. However, little attention has been paid to the dynamics and control of the simultaneous changes in the feed and product specifications. In this study, it is proposed an intelligent control system based on artificial neural network for the extractive process to obtain anhydrous ethanol using ethylene glycol as a solvent. The study considered the changes in the azeotropic feed and the specification of anhydrous ethanol simultaneously, taking both the extractive and recovery columns into account, and keeping the process operating at minimum energy consumption condition. The performance of the intelligent control system was evaluated using Aspen Plus Dynamics™, and the results showed that it is is able to efficiently determine the new setpoints of controllers when facing changes in anhydrous ethanol specification and/or disturbances in the azeotrope feed. The new steady-state is reached in a short time interval (2–4 h, depending on the disturbance type). Based on the integral squared error, integral absolute error, and steady-state error, the results showed that the intelligent control system presented superior performance when compared to conventional control systems. The implementation of the developed control is simple and the existing control structure remains unchanged.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
