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Dergiler / Communications Faculty of Sciences University of Ankara Series B Chemistry and Chemical Engineering / 2025 / Volume: 67 Issue: 2

OPTIMIZED MULTILOOP CONTROL OF THE VAN DE VUSSE REACTOR USING RGA AND NONLINEAR PROGRAMMING

Mojtaba Azizi
Mohammad Amin Ghanavati
Omid Abedi
Sayfa
10–44
Yayın Tarihi
2025-12-23
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

This combined approach leads to more accurate tuning and better dynamic performance, demonstrating its effectiveness for controlling complex chemical systems.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Controlling multivariable, non-isothermal chemical reactors is especially important due to the complex behavior they often exhibit.
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Temel Bulgular & Veri:These factors make achieving accurate and stable control a significant challenge.
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Sonuç & Katkı:This combined approach leads to more accurate tuning and better dynamic performance, demonstrating its effectiveness for controlling complex chemical systems.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Van de Vusse reactor · Multivariable control · Nonlinear Programming

Abstract

ABSTRACT. Controlling multivariable, non-isothermal chemical reactors is especially important due to the complex behavior they often exhibit. In the Van de Vusse reactor, the presence of both parallel and consecutive reactions adds to this complexity by introducing strong temperature dependencies and tight interactions between process variables. These factors make achieving accurate and stable control a significant challenge. This study focuses on enhancing the reactor’s control performance by carefully selecting the most effective input-output pairings and optimizing the controller parameters. In the proposed approach, the most effective input-output pairings for applying multiloop control are first determined using the Relative Gain Array method. Once these pairings are established, the controller parameters for each loop are fine-tuned using nonlinear programming to achieve better overall performance. The simulation results show that the proposed optimization method significantly outperforms traditional manual tuning by improving system response, reducing the time to reach setpoints, and enhancing control stability. The main contribution of this work is the integration of the Relative Gain Array with nonlinear programming to optimally design and tune multiloop controllers for the Van de Vusse process. This combined approach leads to more accurate tuning and better dynamic performance, demonstrating its effectiveness for controlling complex chemical systems.

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Bu Makaleye Atıf Yap

Azizi, M., Ghanavati, M. A., Abedi, O. (2025). OPTIMIZED MULTILOOP CONTROL OF THE VAN DE VUSSE REACTOR USING RGA AND NONLINEAR PROGRAMMING. Communications Faculty of Sciences University of Ankara Series B Chemistry and Chemical Engineering, Volume: 67 Issue: 2, 10–44. https://ajindex.com/articles/1023774

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Kaynakça (13)

  1. Suo, L., Ren, J., Zhao, Z., Zhai, C., Study on the nonlinear dynamics of the continuous stirred tank reactors, Processes, 8 (11) (2020), 1–18, https://doi.org/10.3390/pr8111436.
  2. Hajaya, M. G., Shaqarin, T., Multivariable advanced nonlinear controller for bioethanol production in a non-isothermal fermentation bioreactor, Bioresour. Technol., 348 (2022).
  3. Youssef, A. A. A., Salas, A. H., Al-Harbi, N., Basfer, N. M., Nassr, D. I., Determination of chemical kinetic parameters in Arrhenius equation of constant heating rate: Theoretical method, Alexandria Eng. J., 67 (2023), 461–472, https://doi.org/10.1016/j.aej.2022.12.046.
  4. Petrucci, R. H., Herring, F. G., Madura, J. D., General Chemistry: Principles and Modern Applications, Pearson Prentice Hall, New Jersey, 2010.
  5. Bzioui, S., Channa, R., Robust tracking control for the non-isothermal continuous stirred tank reactor, Int. J. Bioautomation, 24 (2) (2020), 131–142, https://doi.org/10.7546/ijba.2020.24.2.000615.
  6. Amte, V., Nistala, S., Malik, R., Mahajani, S., Attainable regions of reactive distillation-Part III. Complex reaction scheme: Van de Vusse reaction, Chem. Eng. Sci., 66 (11) (2011), 2285–2297, https://doi.org/10.1016/j.ces.2011.02.008.
  7. Sahlodin, A. M., Barton, P. I., Optimal Campaign Continuous Manufacturing, Ind. Eng. Chem. Res., 54 (45) (2015), 11344–11359, https://doi.org/10.1021/acs.iecr.5b01376.
  8. Rothfuss, R., Rudolph, J., Zeitz, M., Flatness based control of a nonlinear chemical reactor model, Automatica, 32 (10) (1996), 1433–1439, https://doi.org/10.1016/0005-1098(96)00090-8.
  9. Raghu, N., Ruchika, Analysis of Van de Vusse Reactor using Model Predictive Control, Int. J. Emerg. Technol. Adv. Eng., 3 (6) (2013), 236–240.
  10. Huilcapi, V. R.-M., Blasco, X., Herrero, J. M., A Loop Pairing Method for Multivariable Control Systems under a Multi-Objective Optimization Approach, IEEE Access, 7 (1) (2019), 81994–82014. Navrátil, P., Pekař, L., Matušů, R., Control of a Multivariable System Using Optimal Control Pairs: A Quadruple-Tank Process, IEEE Access, 8 (2020), 2537–2563, https://doi.org/10.1109/ACCESS.2019.2962302.
  11. Liu, L., Tian, S., Xue, D., Zhang, T., Chen, Y., Zhang, S., A Review of Industrial MIMO Decoupling Control, Automation and Systems, Int. J. Control, 17 (X) (2019), 1–9.
  12. Chen, D., Seborg, D. E., Relative Gain Array Analysis for Uncertain Process Models, AIChE J., 48 (2) (2002), 302–310, https://doi.org/10.1002/aic.690480214.
  13. Machado, V. C., Gabriel, D., Lafuente, J., Baeza, J. A., Cost and effluent q