Adaptive control of continuous polymerization reactor
This study investigates the control of free-radical polymerization reaction of methyl-methacrylate initiated by azo-bis-isobutyronitrile in toluene solvent under isothermal condition. The dynamics of the polymerization reaction in the reactor is represented by a phenomenological mathematical model....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23311916.2022.2086673 |
| _version_ | 1827883118658322432 |
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| author | Muhammad Maaruf Sami El Ferik Magdi S. Mahmoud |
| author_facet | Muhammad Maaruf Sami El Ferik Magdi S. Mahmoud |
| author_sort | Muhammad Maaruf |
| collection | DOAJ |
| description | This study investigates the control of free-radical polymerization reaction of methyl-methacrylate initiated by azo-bis-isobutyronitrile in toluene solvent under isothermal condition. The dynamics of the polymerization reaction in the reactor is represented by a phenomenological mathematical model. The order of the model is reduced using the Hankel singular value decomposition (HSVD) to lessen the computational burden. However, process models are time-varying and exhibit different behaviors at different operating conditions. As a result, a recursive least squares with exponential forgetting factor (RLS-EFF) algorithm is employed to identify the parameters of the reduced-order model. Then, an indirect adaptive minimum degree pole placement control (AMDPP) which provides the desired closed-loop poles is implemented for the identified model. In addition, a continuous-time model reference adaptive control (MRAC) is developed for the reactor. Nevertheless, cost-effectiveness and constraint imposition cannot be achieved with both AMDPP and MRAC. Consequently, an adaptive model predictive control (AMPC) is designed for the identified model to overcome these limitations. Simulation results demonstrate the superiority of the AMPC. |
| first_indexed | 2024-03-12T19:07:02Z |
| format | Article |
| id | doaj.art-3ff6a503140a4e078b01be5d1d4add7a |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-12T19:07:02Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-3ff6a503140a4e078b01be5d1d4add7a2023-08-02T06:08:35ZengTaylor & Francis GroupCogent Engineering2331-19162022-12-019110.1080/23311916.2022.2086673Adaptive control of continuous polymerization reactorMuhammad Maaruf0Sami El Ferik1Magdi S. Mahmoud2Control and Instrumentation Engineering Department Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaControl and Instrumentation Engineering Department Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaControl and Instrumentation Engineering Department Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaThis study investigates the control of free-radical polymerization reaction of methyl-methacrylate initiated by azo-bis-isobutyronitrile in toluene solvent under isothermal condition. The dynamics of the polymerization reaction in the reactor is represented by a phenomenological mathematical model. The order of the model is reduced using the Hankel singular value decomposition (HSVD) to lessen the computational burden. However, process models are time-varying and exhibit different behaviors at different operating conditions. As a result, a recursive least squares with exponential forgetting factor (RLS-EFF) algorithm is employed to identify the parameters of the reduced-order model. Then, an indirect adaptive minimum degree pole placement control (AMDPP) which provides the desired closed-loop poles is implemented for the identified model. In addition, a continuous-time model reference adaptive control (MRAC) is developed for the reactor. Nevertheless, cost-effectiveness and constraint imposition cannot be achieved with both AMDPP and MRAC. Consequently, an adaptive model predictive control (AMPC) is designed for the identified model to overcome these limitations. Simulation results demonstrate the superiority of the AMPC.https://www.tandfonline.com/doi/10.1080/23311916.2022.2086673Polymerization reactorModel order reductionAdaptive controlMinimum degree pole placementModel predictive controlreference adaptive control |
| spellingShingle | Muhammad Maaruf Sami El Ferik Magdi S. Mahmoud Adaptive control of continuous polymerization reactor Cogent Engineering Polymerization reactor Model order reduction Adaptive control Minimum degree pole placement Model predictive control reference adaptive control |
| title | Adaptive control of continuous polymerization reactor |
| title_full | Adaptive control of continuous polymerization reactor |
| title_fullStr | Adaptive control of continuous polymerization reactor |
| title_full_unstemmed | Adaptive control of continuous polymerization reactor |
| title_short | Adaptive control of continuous polymerization reactor |
| title_sort | adaptive control of continuous polymerization reactor |
| topic | Polymerization reactor Model order reduction Adaptive control Minimum degree pole placement Model predictive control reference adaptive control |
| url | https://www.tandfonline.com/doi/10.1080/23311916.2022.2086673 |
| work_keys_str_mv | AT muhammadmaaruf adaptivecontrolofcontinuouspolymerizationreactor AT samielferik adaptivecontrolofcontinuouspolymerizationreactor AT magdismahmoud adaptivecontrolofcontinuouspolymerizationreactor |