One-layer gradient-based MPC + RTO of a propylene/propane splitter

Here, the implementation of the gradient-based Economic MPC (Model Predictive Control) in an industrial distillation system is studied. The approach is an alternative to overcome the conflict between the MPC and RTO (Real Time Optimization) layers in the conventional control structure. The study is...

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Bibliographic Details
Authors: Hinojosa, Aldo Ignacio, Ferramosca, Antonio, González, Alejandro Hernán, Odloak, Darci
Format: article
Status:Published version
Publication Date:2017
Country:Argentina
Institution:Consejo Nacional de Investigaciones Científicas y Técnicas
Repository:CONICET Digital (CONICET)
Language:English
OAI Identifier:oai:ri.conicet.gov.ar:11336/58692
Online Access:http://hdl.handle.net/11336/58692
Access Level:Open access
Keyword:Dynamic Simulation
Economic Model Predictive Control
Propylene Production Unit
Real Time Optimization
https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
Description
Summary:Here, the implementation of the gradient-based Economic MPC (Model Predictive Control) in an industrial distillation system is studied. The approach is an alternative to overcome the conflict between the MPC and RTO (Real Time Optimization) layers in the conventional control structure. The study is based on the rigorous dynamic simulation software (SimSciDynsim®) that reproduces the real system very closely and is able to communicate with Matlab. The gradient of the economic function, is obtained through the sensitivity tool of the real-time optimization package (SimSciROMeo®). In order to study the pros and cons of the new strategy, a propylene distillation system is simulated with both, the proposed approach (one-layer MPC + RTO) and the conventional two-layer hierarchical structure of control and optimization. The results show that, for this particular system, from the performance, stability and disturbance rejection viewpoint, the proposed gradient-based extended control method is equivalent or better than the conventional approach.