Skip to main content

A comparison of different dynamic decoupling methods for a nonlinear MIMO Plant

  • Conference paper
  • First Online:
Trends in Advanced Intelligent Control, Optimization and Automation (KKA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 577))

Included in the following conference series:

Abstract

In the paper two different control systems for nonlinear multi-input multi-output MIMO plants are compared and discussed. Their main objective is to reduce the influence of the plant inputs and outputs. A multi-controller control structure, which contains a set of a dynamic decoupling controllers is compared with a synthetized online nonlinear model predictive controller. Pros and cons of both methods are discussed and presented in series of simulations of control of a selected nonlinear MIMO plant. Te paper ends with some final remarks on a practical implementation of decoupling methods for a nonlinear MIMO plants.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • 1. Arousi F., Predictive control algorithms for linear and nonlinear processes, PhD. Thesis, Budapest, Hungary, (2009)

    Google Scholar 

  • 2. Bańka S., Dworak P., Jaroszewski K., Linear adaptive structure for control of a nonlinear MIMO dynamic plant, International Journal of Applied Mathematics and Computer Science, Vol. 23, No. 1., pp. 47–63 (2013)

    Google Scholar 

  • 3. Bańka S., Dworak P., Jaroszewski K., Design of a multivariable neural controller for control of a nonlinear MIMO plant, International Journal of Applied Mathematics and Computer Science, Vol. 24, No. 2., pp. 357–369 (2014)

    Google Scholar 

  • 4. Bego O., Peric N., Petrovic I., Decoupling multivariable GPC with reference observation. 10th Mediterranean Electromechanical Conference, Vol. II, pp. 819–822 (2000)

    Google Scholar 

  • 5. Chiu Ch-S., A dynamic decoupling approach to robust T-S fuzzy model-based control, IEEE Transactions on Fuzzy Systems, Vol. 22, No. 5, pp. 1088–1100 (2014)

    Google Scholar 

  • 6. Dworak, P., Bańka S.: Efficient algorithm for synthesis of multipurpose control systems with dynamic decoupling. MMAR05, Miedzyzdroje, 345–350 (2005)

    Google Scholar 

  • 7. Dworak P., Pietrusewicz K., Domek S., Improving stability and regulation quality of nonlinear MIMO processes, Methods and Models in Automatic and Robotics, (2009)

    Google Scholar 

  • 8. Dworak, P.: Dynamic decoupling of left-invertible MIMO LTI plants. Archives of Control Science 21(4), 443–459 (2011)

    Google Scholar 

  • 9. Dworak P., Brasel M., Improving quality of regulation of a nonlinear MIMO dynamic plant, Electronics and Electrical Engineering, Vol. 19, No. 7, pp. 3–6 (2013)

    Google Scholar 

  • 10. Dworak, P.: Squaring down plant model and I/O grouping strategies for a dynamic decoupling of left-invertible MIMO plants. Bulletin of the Polish Academy of Sciences,

    Google Scholar 

  • 11. Dworak P., A Type of Fuzzy T-S Controller for a Nonlinear MIMO Dynamic Plant, Elektronika ir elektrotechnika, Vol. 20, No. 5, pp. 8–14 (2014)

    Google Scholar 

  • 12. Dworak P., Jaroszewski K., About Dynamic Decoupling of a Nonlinear MIMO Dynamic Plant, Methods and Models in Automatic and Robotics, Miedzyzdroje, Poland, pp. 106–111 (2014)

    Google Scholar 

  • 13. Dworak P., Dynamic Decoupling of a Nonlinear MIMO Plant, in Aktualne Problemy Automatyki i Robotyki, Eds. Jzefczyk J., Malinowski K., witek J., EXIT, pp. 158–167 (2014)

    Google Scholar 

  • 14. Dworak P., Jaroszewski K., Neural Networks for a Dynamic Decoupling of a Non-linear MIMO Dynamic Plant, Methods and Models in Automatic and Robotics, Miedzyzdroje, Poland, pp. 788–793 (2015)

    Google Scholar 

  • 15. Galindo R., Input/Output Decoupling of Square Linear Systems by Dynamic Two-Parameter Stabilizing Control, Asian Journal of Control, Vol. 18, No. 6, pp. 2310–2316 (2016)

    Google Scholar 

  • 16. Grune L., Pannek J., Nonlinear model predictive control, Springer Verlag, London (2007)

    Google Scholar 

  • 17. Haber R., Bars R., Schmitz U., Predictive control in process engineering,Weinheim, WILEY-VCH (2011)

    Google Scholar 

  • 18. Ben Hariz M., Bouani F., Synthesis and Implementation of a Robust Fixed Low-Order Controller for Uncertain Systems, Arabian Journal for Science and Engineering, Vol. 41, No. 9, pp. 3645–3654 (2016)

    Google Scholar 

  • 19. Huijberts H.J.C., Moog C.H., Pothin R., Input-output decoupling of nonlinear systems by static measurement feedback, Systems & Control Letters, Vol. 39, pp. 109–114 (2000)

    Google Scholar 

  • 20. Isidori A., Nonlinear control systems, New York, Springer-Verlag (1995)

    Google Scholar 

  • 21. Khalil H.K., Nonlinear systems, Prentice Hall (2001)

    Google Scholar 

  • 22. Koumboulis F.N., Skarpetis M.G., Input-output decoupling for linear systems with nonlinear uncertain structure, Journal of the Franklin Institute, Vol. 333(B), No. 4, pp. 593–624 (1996)

    Google Scholar 

  • 23. Koumboulis F.N., Skarpetis M.G., Output feedback decoupling of linear systems with nonlinear uncertain structure, Journal of the Franklin Institute, Vol. 333(B), No. 4, pp. 625–629 (1996)

    Google Scholar 

  • 24. Kueera V., Optimal decoupling controllers revisited, Control and Cybernetics, Vol. 42, No. 1, pp. 139–154, (2013)

    Google Scholar 

  • 25. Liu G.,Wang Z., Mei C., Ding Y., A review of decoupling control based on multiple models, 24th Chinese Control and Decision Conference, pp. 1077–1081 (2012)

    Google Scholar 

  • 26. Oblak S., Skrjanc I., Multivariable fuzzy predictive functional control of a MIMO nonlinear system, Proc. of the 2005 IEEE International Symposium on Intelligent Control, Limassol, Cyprus, pp.1029–1034 (2005)

    Google Scholar 

  • 27. Park K., H2 design of decoupling controllers based on directional interpolations, Joint 48th IEEE CDC and 28th Chinese Control Conference, pp. 5333–5338 (2009)

    Google Scholar 

  • 28. Pereira R.D.O., Veronesi M., Visioli A., Normey-Rico J.E., Torrico B.C.,Implementation and test of a new autotuning method for PID controllers of TITO processes, Control Engineering Practice, Vol. 58, pp. 171–185 (2017)

    Google Scholar 

  • 29. Saniye A., Suleyman K., Decoupling constrained model predictive control of multicomponent packed distillation column, World Applied Science Journal, Vol. 13, No. 3, pp. 517–530 (2011)

    Google Scholar 

  • 30. Schmitz U., Haber R., Arousi F., et al., Decoupling predictive control by error dependent tuning of the weighting factors, Process Control Conference, Sterbskie Pleso, pp. 131–140 (2007)

    Google Scholar 

  • 31. Wang X., Li S., Wang Z., Yue H.,Multiple Models Neural Network Decoupling Controller for a Nonlinear System, LNCS, Vol. 3174, pp. 175–180 (2004)

    Google Scholar 

  • 32. Wang X., Yang H., Wang B., Multiple models fuzzy decoupling controller for a nonlinear systems, LNAI, Vol. 4223, pp. 860–863 (2006)

    Google Scholar 

  • 33. Wise D.A., English J.W., Tank and wind tunnel test for a drillship with dynamic position control, Offshore Tehnology Conference, TX Dallas (1975)

    Google Scholar 

  • 34. Zabert K., Haber R., Improvement of the decoupling effect of the predictive controller GPC and PFC by parameter adaptation, 18th International Conference on Process Control, Tatranska Lomnica, Slovakia, pp. 419–426 (2011)

    Google Scholar 

  • 35. Zermani M.A., Feki E., Mami A., Self tuning weighting factor to decoupling control for incubator system, International Journal of Information Technology, Control and Automation, Vol. 2, No. 3., pp. 67–83 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paweł Dworak .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Dworak, P., Brasel, M., Ghosh, S. (2017). A comparison of different dynamic decoupling methods for a nonlinear MIMO Plant. In: Mitkowski, W., Kacprzyk, J., Oprzędkiewicz, K., Skruch, P. (eds) Trends in Advanced Intelligent Control, Optimization and Automation. KKA 2017. Advances in Intelligent Systems and Computing, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-60699-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60699-6_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60698-9

  • Online ISBN: 978-3-319-60699-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics