eprintid: 10858
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/08/58
datestamp: 2023-11-09 16:37:28
lastmod: 2023-11-09 16:37:28
status_changed: 2023-11-09 16:32:22
type: article
metadata_visibility: show
creators_name: Tuan, T.T.
creators_name: Tufa, L.D.
creators_name: Mutalib, M.I.A.
creators_name: Ramli, N.M.
title: Optimal operation of a process by integrating dynamic economic optimization and model predictive control formulated with empirical model
ispublished: pub
keywords: Controllers; Kalman filters; Predictive control systems; Profitability; State feedback, Advanced control; Depropanizer; Different time scale; Economic optimization; Empirical model; Integrate RTO-MPC; Objective functions; Optimal operation, Model predictive control
note: cited By 1
abstract: In advanced control, a control target tracks the set points and tends to achieve optimal operation of a process. Model predictive control (MPC) is used to track the set points. When the set points correspond to an optimum economic trajectory that is sent from an economic layer, the process will be gradually reaching the optimal operation. This study proposes the integration of an economic layer and MPC layer to solve the problem of different time scale and unreachable set points. Both layers require dynamic models that are subject to objective functions. The prediction output of a model is not always asymptotically equal to the measured output of a process. Therefore, Kalman filter is proposed as a state feedback to the two-layer integration. The proposed controller only considers the linear empirical model and the inherent model is identified by system identification, which is assumed to be an ample representation of the process. A depropanizer process case study has been used for demonstration of the proposed technique. The result shows that the proposed controller tends to improve the profit of the process smoothly and continuously, until the process reaches an asymptotically maximum profit point. © 2018 Institute of Automatic Control - Silesian University of Technology. All rights reserved.
date: 2018
publisher: Polish Academy of Sciences
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046713070&doi=10.24425%2f119076&partnerID=40&md5=1c9a7d0e5a5285ef9edf5e11180106c4
id_number: 10.24425/119076
full_text_status: none
publication: Archives of Control Sciences
volume: 28
number: 1
pagerange: 35-50
refereed: TRUE
issn: 12302384
citation:   Tuan, T.T. and Tufa, L.D. and Mutalib, M.I.A. and Ramli, N.M.  (2018) Optimal operation of a process by integrating dynamic economic optimization and model predictive control formulated with empirical model.  Archives of Control Sciences, 28 (1).  pp. 35-50.  ISSN 12302384