Performance comparison of different control strategies for heat exchanger networks

In this article, the dynamic responses of heat exchanger networks to disturbance and setpoint change were studied. Various control strategies, including: proportional integral, model predictive control, passivity approach, and passivity-based model predictive control were used to monitor all outlet...

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Main Authors: Mahitthimahawong Siwaporn, Chotvisut Yada, Srinophakun Thongchai
Format: Article
Language:English
Published: Sciendo 2018-03-01
Series:Polish Journal of Chemical Technology
Subjects:
Online Access:https://doi.org/10.2478/pjct-2018-0003
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spelling doaj-685c0168219d4ef3a520666ff20ac24f2021-09-05T14:01:00ZengSciendoPolish Journal of Chemical Technology1899-47412018-03-01201132010.2478/pjct-2018-0003pjct-2018-0003Performance comparison of different control strategies for heat exchanger networksMahitthimahawong Siwaporn0Chotvisut Yada1Srinophakun Thongchai2Kasetsart University, Department of Chemical Engineering, 50 Ngamwongwan Rd., Ladyao, Jatujak, Bangkok10900, ThailandKing Mongkut’s University of Technology Thonburi, Chemical Engineering Practice School, 126 Pracha-utid Road, Bangmod, Thoongkru, Bangkok10140, ThailandKasetsart University, Department of Chemical Engineering, 50 Ngamwongwan Rd., Ladyao, Jatujak, Bangkok10900, ThailandIn this article, the dynamic responses of heat exchanger networks to disturbance and setpoint change were studied. Various control strategies, including: proportional integral, model predictive control, passivity approach, and passivity-based model predictive control were used to monitor all outlet temperatures. The performance of controllers was analyzed through two procedures: 1) inducing a ±5% step disturbance in the supply temperature, or 2) tracking a ±5°C target temperature. The performance criteria used to evaluate these various control modes was settling time and percentage overshoot. According to the results, the passivity-based model predictive controllers produced the best performance to reject the disturbance and the model predictive control proved to be the best controller to track the setpoint. Whereas, the ensuing performance results of both the PI and passivity controllers were discovered to be only acceptable.https://doi.org/10.2478/pjct-2018-0003controldynamic simulationperformanceprocess controlstability
collection DOAJ
language English
format Article
sources DOAJ
author Mahitthimahawong Siwaporn
Chotvisut Yada
Srinophakun Thongchai
spellingShingle Mahitthimahawong Siwaporn
Chotvisut Yada
Srinophakun Thongchai
Performance comparison of different control strategies for heat exchanger networks
Polish Journal of Chemical Technology
control
dynamic simulation
performance
process control
stability
author_facet Mahitthimahawong Siwaporn
Chotvisut Yada
Srinophakun Thongchai
author_sort Mahitthimahawong Siwaporn
title Performance comparison of different control strategies for heat exchanger networks
title_short Performance comparison of different control strategies for heat exchanger networks
title_full Performance comparison of different control strategies for heat exchanger networks
title_fullStr Performance comparison of different control strategies for heat exchanger networks
title_full_unstemmed Performance comparison of different control strategies for heat exchanger networks
title_sort performance comparison of different control strategies for heat exchanger networks
publisher Sciendo
series Polish Journal of Chemical Technology
issn 1899-4741
publishDate 2018-03-01
description In this article, the dynamic responses of heat exchanger networks to disturbance and setpoint change were studied. Various control strategies, including: proportional integral, model predictive control, passivity approach, and passivity-based model predictive control were used to monitor all outlet temperatures. The performance of controllers was analyzed through two procedures: 1) inducing a ±5% step disturbance in the supply temperature, or 2) tracking a ±5°C target temperature. The performance criteria used to evaluate these various control modes was settling time and percentage overshoot. According to the results, the passivity-based model predictive controllers produced the best performance to reject the disturbance and the model predictive control proved to be the best controller to track the setpoint. Whereas, the ensuing performance results of both the PI and passivity controllers were discovered to be only acceptable.
topic control
dynamic simulation
performance
process control
stability
url https://doi.org/10.2478/pjct-2018-0003
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AT chotvisutyada performancecomparisonofdifferentcontrolstrategiesforheatexchangernetworks
AT srinophakunthongchai performancecomparisonofdifferentcontrolstrategiesforheatexchangernetworks
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