HVAC multivariable system modelling and control

Heating, Ventilation and Air Conditioning (HVAC) is a multivariable process where any alteration with one system input affects most or all of the system’s outputs simultaneously. Owing to its comprehensiveness, a readily derived multivariable HVAC mathematical model is selected for this work, mainly...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Touqan, Basim (author)
مؤلفون آخرون: Abdul-Ameer, Alaa (author), Salameh, Muna (author)
منشور في: 2022
الوصول للمادة أونلاين:https://bspace.buid.ac.ae/handle/1234/2945
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author Touqan, Basim
author2 Abdul-Ameer, Alaa
Salameh, Muna
author2_role author
author
author_facet Touqan, Basim
Abdul-Ameer, Alaa
Salameh, Muna
author_role author
dc.creator.none.fl_str_mv Touqan, Basim
Abdul-Ameer, Alaa
Salameh, Muna
dc.date.none.fl_str_mv 2022
2025-05-08T10:59:29Z
2025-05-08T10:59:29Z
dc.identifier.none.fl_str_mv https://bspace.buid.ac.ae/handle/1234/2945
dc.language.none.fl_str_mv en
dc.title.none.fl_str_mv HVAC multivariable system modelling and control
dc.type.none.fl_str_mv Article
description Heating, Ventilation and Air Conditioning (HVAC) is a multivariable process where any alteration with one system input affects most or all of the system’s outputs simultaneously. Owing to its comprehensiveness, a readily derived multivariable HVAC mathematical model is selected for this work, mainly a hybrid distributed-lumped parameters model. As the transfer function matrix was not established in the selected HVAC model, it was exclusively developed in this study, using the time domain graphical responses of the chosen model. Based on the developed transfer function matrix, a conceptual two-step approach was followed to control HVAC model performance. The first was decoupling the interactions that affect all the system outputs, and the second was designing proper PID controllers for each decoupled loop similar to those used for single input single output (SISO) systems. A direct Nyquist Array (DNA) multivariable control strategy was used for this purpose and successfully decoupled the HVAC system into three separate (SISO) loops. Three PID controllers afterwards were applied for each decoupled loop. The results showed quite decoupled system outputs with a minor coupling percentage so that any change in a system input only affected the corresponding system output. The output responses are also underdamped with almost zero steady-state error confirming the effectiveness of the selected PID parameters. The values of steady-state responses are obtained in (10– 15) s compared with (200–600) s of open-loop response time. However, various overshoot percentages in the responses are encountered but are relatively small, with a short settling time, so they don’t affect the thermal comfort of the ventilated volume. System stability using the Nyquist criterion has also been examined and found to satisfy the criterion. The multivariable DNA control technique and the SISO closed-loop PID controllers have shown the capability to suppress external disturbances and restore the system to its original functional steady-state values.
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network_name_str The British University in Dubai repository
oai_identifier_str oai:bspace.buid.ac.ae:1234/2945
publishDate 2022
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spelling HVAC multivariable system modelling and controlTouqan, BasimAbdul-Ameer, AlaaSalameh, MunaHeating, Ventilation and Air Conditioning (HVAC) is a multivariable process where any alteration with one system input affects most or all of the system’s outputs simultaneously. Owing to its comprehensiveness, a readily derived multivariable HVAC mathematical model is selected for this work, mainly a hybrid distributed-lumped parameters model. As the transfer function matrix was not established in the selected HVAC model, it was exclusively developed in this study, using the time domain graphical responses of the chosen model. Based on the developed transfer function matrix, a conceptual two-step approach was followed to control HVAC model performance. The first was decoupling the interactions that affect all the system outputs, and the second was designing proper PID controllers for each decoupled loop similar to those used for single input single output (SISO) systems. A direct Nyquist Array (DNA) multivariable control strategy was used for this purpose and successfully decoupled the HVAC system into three separate (SISO) loops. Three PID controllers afterwards were applied for each decoupled loop. The results showed quite decoupled system outputs with a minor coupling percentage so that any change in a system input only affected the corresponding system output. The output responses are also underdamped with almost zero steady-state error confirming the effectiveness of the selected PID parameters. The values of steady-state responses are obtained in (10– 15) s compared with (200–600) s of open-loop response time. However, various overshoot percentages in the responses are encountered but are relatively small, with a short settling time, so they don’t affect the thermal comfort of the ventilated volume. System stability using the Nyquist criterion has also been examined and found to satisfy the criterion. The multivariable DNA control technique and the SISO closed-loop PID controllers have shown the capability to suppress external disturbances and restore the system to its original functional steady-state values.2025-05-08T10:59:29Z2025-05-08T10:59:29Z2022Articlehttps://bspace.buid.ac.ae/handle/1234/2945enoai:bspace.buid.ac.ae:1234/29452025-05-08T10:59:30Z
spellingShingle HVAC multivariable system modelling and control
Touqan, Basim
title HVAC multivariable system modelling and control
title_full HVAC multivariable system modelling and control
title_fullStr HVAC multivariable system modelling and control
title_full_unstemmed HVAC multivariable system modelling and control
title_short HVAC multivariable system modelling and control
title_sort HVAC multivariable system modelling and control
url https://bspace.buid.ac.ae/handle/1234/2945