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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Online Access: | https://doi.org/10.2478/pjct-2018-0003 |
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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 |
work_keys_str_mv |
AT mahitthimahawongsiwaporn performancecomparisonofdifferentcontrolstrategiesforheatexchangernetworks AT chotvisutyada performancecomparisonofdifferentcontrolstrategiesforheatexchangernetworks AT srinophakunthongchai performancecomparisonofdifferentcontrolstrategiesforheatexchangernetworks |
_version_ |
1717810965972516864 |