Robust Model Predictive Control of Heat Exchangers

The paper attempts to show that using the robust model-based predictive control (RMPC) strategy for control of thermal processes can lead to energy savings in comparison with classical control approaches. RMPC is applied for control of a tubular heat exchanger that is used for pre-heating petroleum...

Full description

Bibliographic Details
Main Authors: M. Bakošová, J. Oravec
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2012-09-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/7241
id doaj-ada34da60b504951b2001d1e129e4619
record_format Article
spelling doaj-ada34da60b504951b2001d1e129e46192021-02-22T21:02:28ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162012-09-012910.3303/CET1229245Robust Model Predictive Control of Heat ExchangersM. BakošováJ. OravecThe paper attempts to show that using the robust model-based predictive control (RMPC) strategy for control of thermal processes can lead to energy savings in comparison with classical control approaches. RMPC is applied for control of a tubular heat exchanger that is used for pre-heating petroleum by hot water. The heat exchanger is a nonlinear system with time delay and uncertainty. The control objective is to keep the output temperature of the heated stream at a reference value and minimize the energy consumption needed for petroleum heating. The advantage of RMPC is that it is the optimisation based strategy, the control input and controlled outputs constraints are directly included into the synthesis and uncertainty of the process model is taken into account. RMPC of the heat exchanger is compared with the classical optimal linear quadratic (LQ) control by simulations experiments. In the presence of uncertainty and boundaries on control inputs, using the RMPC approach increases the quality of the control performance and decreases energy supplied to the heating medium.https://www.cetjournal.it/index.php/cet/article/view/7241
collection DOAJ
language English
format Article
sources DOAJ
author M. Bakošová
J. Oravec
spellingShingle M. Bakošová
J. Oravec
Robust Model Predictive Control of Heat Exchangers
Chemical Engineering Transactions
author_facet M. Bakošová
J. Oravec
author_sort M. Bakošová
title Robust Model Predictive Control of Heat Exchangers
title_short Robust Model Predictive Control of Heat Exchangers
title_full Robust Model Predictive Control of Heat Exchangers
title_fullStr Robust Model Predictive Control of Heat Exchangers
title_full_unstemmed Robust Model Predictive Control of Heat Exchangers
title_sort robust model predictive control of heat exchangers
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2012-09-01
description The paper attempts to show that using the robust model-based predictive control (RMPC) strategy for control of thermal processes can lead to energy savings in comparison with classical control approaches. RMPC is applied for control of a tubular heat exchanger that is used for pre-heating petroleum by hot water. The heat exchanger is a nonlinear system with time delay and uncertainty. The control objective is to keep the output temperature of the heated stream at a reference value and minimize the energy consumption needed for petroleum heating. The advantage of RMPC is that it is the optimisation based strategy, the control input and controlled outputs constraints are directly included into the synthesis and uncertainty of the process model is taken into account. RMPC of the heat exchanger is compared with the classical optimal linear quadratic (LQ) control by simulations experiments. In the presence of uncertainty and boundaries on control inputs, using the RMPC approach increases the quality of the control performance and decreases energy supplied to the heating medium.
url https://www.cetjournal.it/index.php/cet/article/view/7241
work_keys_str_mv AT mbakosova robustmodelpredictivecontrolofheatexchangers
AT joravec robustmodelpredictivecontrolofheatexchangers
_version_ 1724256303527755776