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SKT içeren çok değişkenli bir sürecin matematiksel modellenmesi ve dinamik etkileşim giderme

Year 2018, Volume: 24 Issue: 2, 219 - 225, 30.04.2018

Abstract

Bu makalede, bir sürekli karıştırılan tank (SKT)
içeren sıcaklık ve debi sürecinin matematiksel modeli ve dinamik etkileşim giderici
tasarımı sunulmuştur. İki doğrusal olmayan diferansiyel denklemden oluşan
dinamik matematiksel model geliştirilmiştir. Çok değişkenli (ÇD) sistem modeli,
döngü etkileşimlerini dinamik yöntemle gidermeyi kolaylaştırmak için
doğrusallaştırılarak transfer fonksiyonlarıyla ifade edilmiştir. Dinamik
etkileşim giderme tasarımı elde edilen doğrusallaştırılmış model yardımıyla
gerçekleştirilmiş ve döngülerin etkileşimlerinin ortadan kaldırılarak sürecin
ayrıştırılmış tek döngülü geri beslemeli denetim için uygun hale getirildiği
gösterilmiştir.

References

  • Salehi S, Shahrokhi M. “Adaptive fuzzy backstepping approach for temperature control of continuous stirred tank reactors”. Fuzzy Sets and Systems, 160(12), 1804-1818, 2009.
  • Cloutier JR, Stansbery DT. “Control of a continuously stirred tank reactor using an asymmetric solution of the state-dependent Riccati equation”. IEEE International Conference on Control Applications, Hawaii, USA, 22-27 August 1999.
  • Yu DL, Gomm JB. “Implementation of neural network predictive control to a multivariable chemical reactor”. Control Engineering Practice, 11(11), 1315-1323, 2003.
  • Hoang H, Couenne F, Jallut C, Le Gorrec Y. “Lyapunov based control for non-isothermal continuous stirred tank reactor”. IFAC Proceedings Volumes, 41(2), 3854-3858, 2008.
  • Alvarez-Ramirez J, Morales A. “PI control of continuously stirred tank reactors: stability and performance”. Chemical Engineering Science, 55(22), 5497-5507, 2000.
  • Alvarez-Ramirez J, Suarez R, Femat R. “Control of continuous-stirred tank reactors: stabilization with unknown reaction rates”. Chemical Engineering Science, 51(17), 4183-4188, 1996.
  • Zhang T, Guay M. “Adaptive nonlinear control of continuously stirred tank reactor systems”. IEEE American Control Conference, Arlington, USA, 25-27 June 2001.
  • Tokuda M, Yamamoto T, Monden Y. “A design of multiloop PID controllers with neural-net based decoupler”. IEEE International Symposium on Intelligent Control, Vancouver, Canada, 30 October 2002.
  • Numsomran A, Wongkhum T, Suksri T, Nilas P, Chaoraingern J. “Design of decoupled controller for TITO system using characteristic ratio assignment”. ICCAS'07 International Conference on Control, Automation and Systems, Seoul, Korea, 17-20 October 2007.
  • Qinling Z, Zhiqiang G. “On decoupling control of uncertain and multivariable systems with time delays”. SICE 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, Hangzhou, China, 28-30 July 2015.
  • Dym C. Principles of Mathematical Modeling. London, UK, Elsevier Academic Press, 2004.
  • Seborg DE, Mellichamp DA, Edgar TF, Doyle III, FJ. Process Dynamics and Control. New York, USA, John Wiley & Sons, 2010.
  • Janevska G. “Mathematical Modeling of Pump System”. EIIC the 2nd Electronic International Interdisciplinary Conference, Zilina, Czech Republic, 2-6 September 2013.
  • Charles MO, Oku DE, Faithpraise FO, Obot EP. “Simulation and control of PMDC motor current and torque”. International Journal of Advanced Scientific and Technical Research, 5(7), 367-375, 2015.
  • Bernard A. Speed Control of Separately Excited DC Motor Using Artificial Intelligent Approach. PhD Thesis, University Tun Hussein Onn Malaysia, 2013.
  • Smith CA, Corripio AB. Principles and Practice of Automatic Process Control. New York, USA, Wiley, 2005.
  • Cochin I, Cadwallender W. Analysis and Design of Dynamic Systems. Prentice Hall, Reading, MA, USA, 1997.
  • Nijmeijer H, Respondek W. “Dynamic input-output decoupling of nonlinear control systems”. IEEE Transactions on Automatic Control, 33(11), 1065-1070, 1988.

Mathematical modeling and dynamic decoupling of a multivariable process with a CST

Year 2018, Volume: 24 Issue: 2, 219 - 225, 30.04.2018

Abstract

In this paper, mathematical modeling and dynamic
decoupler design of a temperature and flow rate process with a continuously
stirred tank (CST) is presented. A dynamic mathematical model of the process
that consists of two nonlinear differential equations is developed. The
multivariable (MV) system model is linearized to make the elimination of loop
interaction easier through dynamic decoupling and expressed in terms of system
transfer functions. Dynamic decoupling is designed using obtained linearized
model and it is shown that loop interactions are eliminated making the process
suitable for decomposed single loop feedback controllers.

References

  • Salehi S, Shahrokhi M. “Adaptive fuzzy backstepping approach for temperature control of continuous stirred tank reactors”. Fuzzy Sets and Systems, 160(12), 1804-1818, 2009.
  • Cloutier JR, Stansbery DT. “Control of a continuously stirred tank reactor using an asymmetric solution of the state-dependent Riccati equation”. IEEE International Conference on Control Applications, Hawaii, USA, 22-27 August 1999.
  • Yu DL, Gomm JB. “Implementation of neural network predictive control to a multivariable chemical reactor”. Control Engineering Practice, 11(11), 1315-1323, 2003.
  • Hoang H, Couenne F, Jallut C, Le Gorrec Y. “Lyapunov based control for non-isothermal continuous stirred tank reactor”. IFAC Proceedings Volumes, 41(2), 3854-3858, 2008.
  • Alvarez-Ramirez J, Morales A. “PI control of continuously stirred tank reactors: stability and performance”. Chemical Engineering Science, 55(22), 5497-5507, 2000.
  • Alvarez-Ramirez J, Suarez R, Femat R. “Control of continuous-stirred tank reactors: stabilization with unknown reaction rates”. Chemical Engineering Science, 51(17), 4183-4188, 1996.
  • Zhang T, Guay M. “Adaptive nonlinear control of continuously stirred tank reactor systems”. IEEE American Control Conference, Arlington, USA, 25-27 June 2001.
  • Tokuda M, Yamamoto T, Monden Y. “A design of multiloop PID controllers with neural-net based decoupler”. IEEE International Symposium on Intelligent Control, Vancouver, Canada, 30 October 2002.
  • Numsomran A, Wongkhum T, Suksri T, Nilas P, Chaoraingern J. “Design of decoupled controller for TITO system using characteristic ratio assignment”. ICCAS'07 International Conference on Control, Automation and Systems, Seoul, Korea, 17-20 October 2007.
  • Qinling Z, Zhiqiang G. “On decoupling control of uncertain and multivariable systems with time delays”. SICE 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, Hangzhou, China, 28-30 July 2015.
  • Dym C. Principles of Mathematical Modeling. London, UK, Elsevier Academic Press, 2004.
  • Seborg DE, Mellichamp DA, Edgar TF, Doyle III, FJ. Process Dynamics and Control. New York, USA, John Wiley & Sons, 2010.
  • Janevska G. “Mathematical Modeling of Pump System”. EIIC the 2nd Electronic International Interdisciplinary Conference, Zilina, Czech Republic, 2-6 September 2013.
  • Charles MO, Oku DE, Faithpraise FO, Obot EP. “Simulation and control of PMDC motor current and torque”. International Journal of Advanced Scientific and Technical Research, 5(7), 367-375, 2015.
  • Bernard A. Speed Control of Separately Excited DC Motor Using Artificial Intelligent Approach. PhD Thesis, University Tun Hussein Onn Malaysia, 2013.
  • Smith CA, Corripio AB. Principles and Practice of Automatic Process Control. New York, USA, Wiley, 2005.
  • Cochin I, Cadwallender W. Analysis and Design of Dynamic Systems. Prentice Hall, Reading, MA, USA, 1997.
  • Nijmeijer H, Respondek W. “Dynamic input-output decoupling of nonlinear control systems”. IEEE Transactions on Automatic Control, 33(11), 1065-1070, 1988.
There are 18 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

Tolgay Kara 0000-0003-3991-8524

Hazhar Rasul This is me 0000-0002-4293-5352

Publication Date April 30, 2018
Published in Issue Year 2018 Volume: 24 Issue: 2

Cite

APA Kara, T., & Rasul, H. (2018). Mathematical modeling and dynamic decoupling of a multivariable process with a CST. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 24(2), 219-225.
AMA Kara T, Rasul H. Mathematical modeling and dynamic decoupling of a multivariable process with a CST. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. April 2018;24(2):219-225.
Chicago Kara, Tolgay, and Hazhar Rasul. “Mathematical Modeling and Dynamic Decoupling of a Multivariable Process With a CST”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 24, no. 2 (April 2018): 219-25.
EndNote Kara T, Rasul H (April 1, 2018) Mathematical modeling and dynamic decoupling of a multivariable process with a CST. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 24 2 219–225.
IEEE T. Kara and H. Rasul, “Mathematical modeling and dynamic decoupling of a multivariable process with a CST”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 24, no. 2, pp. 219–225, 2018.
ISNAD Kara, Tolgay - Rasul, Hazhar. “Mathematical Modeling and Dynamic Decoupling of a Multivariable Process With a CST”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 24/2 (April 2018), 219-225.
JAMA Kara T, Rasul H. Mathematical modeling and dynamic decoupling of a multivariable process with a CST. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2018;24:219–225.
MLA Kara, Tolgay and Hazhar Rasul. “Mathematical Modeling and Dynamic Decoupling of a Multivariable Process With a CST”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 24, no. 2, 2018, pp. 219-25.
Vancouver Kara T, Rasul H. Mathematical modeling and dynamic decoupling of a multivariable process with a CST. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2018;24(2):219-25.

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