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Computational Intelligence in Engineering pp 75–86Cite as

New Principles and Adequate Robust Control Methods for Artificial Pancreas

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 313))

Abstract

The current work is a short review of the research results obtained by the Biomedical Engineering laboratory of the Control Engineering and Information Technology Department, Budapest University of Technology and Economics (BME) in the field of automatic control of Type I diabetes mellitus, and mainly is focused on the PhD dissertation written by the first author [1]. The topic focuses on modeling formalisms and implementation of robust control algorithms for optimal insulin dosage in case of Type I diabetes patients. Regarding modelling concepts, an extension of the modified Bergman minimal model, the analytical investigation of the high complexity Sorensen-model and model synthesis of a novel molecular-based model are described. From robust control methods implementation firstly, the minimax method is applied and is described that its limitations can be spanned using Gröbner basis. Secondly, the graphical interpretation of the H inf method under Mathematica program is extended with disturbance rejection criteria. Thirdly, an LPV (Linear Parameter Varying) type robust control method is described for the high complexity Sorensen-model; hence it is possible to deal directly with the non-linear model itself. Finally, actual research tasks are summarized related to the previously mentioned topics and further research directions are formulated.

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References

  1. Kovács, L.: New Principles and Adequte Control Methods for Insulin Optimization in Case of Type I Diabetes Mellitus, PhD Thesis (in Hungarian) Budapest University of Technology and Economics, Hungary (2008)

    Google Scholar 

  2. Wild, S., Roglic, G., Green, A., Sicree, R., King, H.: Global Prevalence of Diabetes - Estimates for the year 2000 and projections for 2030. Diabetes Care 27(5), 1047–1053 (2004)

    Article  Google Scholar 

  3. Fonyó, A., Ligeti, E.: Physiology (in Hungarian) Medicina, Budapest (2008)

    Google Scholar 

  4. Hernjak, N., Doyle III, F.J.: Glucose Control Design Using Nonlinearity Assessment Techniques. AIChE Journal 51(2), 544–554 (2005)

    Article  Google Scholar 

  5. Parker, R.S., Doyle III, F.J., Ward, J.H., Peppas, N.A.: Robust H_∞ Glucose Control in Diabetes Using a Physiological Model. AIChE Journal 46(12), 2537–2549 (2000)

    Article  Google Scholar 

  6. Ruiz-Velazquez, E., Femat, R., Campos-Delgado, D.U.: Blood Glucose Control for Type I Diabetes Mellitus: A Robust Tracking H ∞  Problem. Elsevier Control Engineering Practice 12, 1179–1195 (2004)

    Article  Google Scholar 

  7. Chee, F., Tyrone, F.: Closed-Loop Control of Blood Glucose. LNCS, vol. 368. Springer, Berlin (2007)

    Google Scholar 

  8. Bergman, B.N., Ider, Y.Z., Bowden, C.R., Cobelli, C.: Quantitive Estimation of Insulin Sensitivity. American Journal of Physiology 236, 667–677 (1979)

    Google Scholar 

  9. Bergman, R.N., Philips, L.S., Cobelli, C.: Physiologic Evaluation of Factors Controlling Glucose Tolerance in Man. Journal of Clinical Investigation 68, 1456–1467 (1981)

    Article  Google Scholar 

  10. Fernandez, M., Acosta, D., Villasana, M., Streja, D.: Enhancing Parameter Precision and the Minimal Modeling Approach in Type I Diabetes. In: Proceedings of 26th IEEE EMBS Annual International Conference, San Francisco, USA, pp. 797–800 (2004)

    Google Scholar 

  11. Morris, H.C., O’Reilly, B., Streja, D.: A New Biphasic Minimal Model. In: Proceedings of 26th IEEE EMBS Annual International Conference, San Francisco, USA, pp. 782–785 (2004)

    Google Scholar 

  12. de Gaetano, A., Arino, O.: Some Considerations on the Mathematical Modeling of the Intra-Venous Glucose Tolerance Test. Journal of Mathematical Biology 40, 136–168 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  13. Juhász, C.: Medical Application of Adaptive Control, Supporting Insulin-Therapy in case of Diabetes Mellitus. PhD dissertation (in Hungarian), Budapest University of Technology and Economics, Hungary (1997)

    Google Scholar 

  14. Roy, A., Parker, R.S.: Mixed Meal Modeling and Disturbance Rejection in Type I Diabetic Patients. In: Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, USA, pp. 323–326 (2006)

    Google Scholar 

  15. Roy, A., Parker, R.S.: Dynamic Modeling of Free Fatty Acid, Glucose, and Insulin: An Extended “Minimal Model”. Diabetes Technology & Therapeutics 8, 617–626 (2006)

    Article  Google Scholar 

  16. Dalla Man, C., Rizza, R.A., Cobelli, C.: Meal Simulation Model of the Glucose-Insulin System. IEEE Transactions on Biomedical Engineering 54(10), 1740–1749 (2007)

    Article  Google Scholar 

  17. Hovorka, R., Shojaee-Moradie, F., Carroll, P.V., Chassin, L.J., Gowrie, I.J., Jackson, N.C., Tudor, R.S., Umpleby, A.M., Jones, R.H.: Partitioning Glucose Distribution/Transport, Disposal, and Endogenous Production during IVGTT. American Journal Physiology Endocrinology Metabolism 282, 992–1007 (2002)

    Google Scholar 

  18. Sorensen, J.T.: A Physiologic Model of Glucose Metabolism is Man and Its use to Design and Assess Improved Insulin Therapies for Diabetes. PhD dissertation, Massachusetts Institute of Technology, USA (1985)

    Google Scholar 

  19. Liu, W., Fusheng, T.: Modeling a Simplified Regulatory System of Blood Glucose at Molecular Levels. Journal of Theoretical Biology 252, 608–620 (2008)

    Article  Google Scholar 

  20. Parker, R.S., Doyle III, F.J., Peppas, N.A.: The Intravenous Route to Blood Glucose Control. A Review of Control Algorithms for Noninvasive Monitoring and Regulation in Type I Diabetic Patients. In: IEEE Engineering in Medicine and Biology, pp. 65–73 (2001)

    Google Scholar 

  21. Chee, F., Fernando, T.L., Savkin, A.V., van Heeden, V.: Expert PID Control System for Blood Glucose Control in Critically Ill Patients. IEEE Transactions on Information Technology in Biomedicine 7(4), 419–425 (2003)

    Article  Google Scholar 

  22. Dazzi, D., Taddei, F., Gavarini, A., Uggeri, E., Negro, R., Pezzarossa, A.: The Control of Blood Glucose in the Critical Diabetic Patient: A Neuro-Fuzzy Method. Journal of Diabetes and Its Complications 15, 80–87 (2001)

    Article  Google Scholar 

  23. Palerm, C.C.: Drug Infusion Control: An Extended Direct Model Reference Adaptive Control Strategy. PhD thesis, Troy, New York (2003)

    Google Scholar 

  24. Hovorka, R.: Management of Diabetes using Adaptive Control. International Journal of Adaptive Control and Signal Processing (2004)

    Google Scholar 

  25. Hovorka, R., Canonico, V., Chassin, L.J., Haueter, U., Massi-Benedetti, M., Orsini Federici, M., Pieber, T.R., Schaller, H.C., Schaupp, L., Vering, T., Wilinska, M.E.: Nonlinear Model Predictive Control of Glucose Concentration in Subjects with Type 1 Diabetes. Physiological Measurement 25, 905–920 (2004)

    Article  Google Scholar 

  26. Kovács, L.: Extension of the Bergman Model – Possible Generalization of the Glucose-Insulin Interaction? Periodica Politechnica Electrical Engineering Budapest 50(1-2), 23–32 (2006)

    Google Scholar 

  27. Kovács, L., Kulcsár, B.: LPV Modeling of Type 1 Diabetes Mellitus. In: Proceedings of the 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, Budapest, Hungary, pp. 163–173 (2007)

    Google Scholar 

  28. Kovács, L., Kulcsár, B.: Robust and Optimal Blood-Glucose Control in Diabetes Using Linear Parameter Varying paradigms. In: Recent Advances in Biomedical Engineering, In-Tech. (in press, 2010)

    Google Scholar 

  29. Kovács, L., György, A., Almássy, Z., Benyó, Z.: Analyzing a Novel Model of Human Blood Glucose System at Molecular Levels. In: Proceedings of the 10th European Control Conference, Budapest, Hungary, pp. 2494–2499 (2009)

    Google Scholar 

  30. Paláncz, B., Kovács, L.: Application of Computer Algebra to Glucose-Insulin Control in H2/H ∞  Space Using Mathematica. Periodica Politechnica Electrical Engineering Budapest 50(1-2), 33–45 (2006)

    Google Scholar 

  31. Kovács, L., Paláncz, B.: Glucose-Insulin Control of Type1 Diabetic Patients in H2/H ∞  Space via Computer Algebra. In: Anai, H., Horimoto, K., Kutsia, T. (eds.) AB 2007. LNCS, vol. 4545, pp. 95–109. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  32. Kovács, L., Paláncz, B., Borbély, E., Benyó, Z., Benyó, B.: Robust Control Techniques and its Graphical Representation in case of Type I Diabetes using Mathematica. In: Proceedings of the 8th International Symposium on Applied Machine Intelligence and Informatics, Herlany, Slovakia, pp. 71–75 (2010)

    Google Scholar 

  33. Kovács, L., Kulcsár, B., Benyó, Z.: On The Use Of Robust Servo Control In Diabetes Under Intensive Care. In: Proceedings of the 3rd Romanian-Hungarian Joint Symposium on Applied Computational Intelligence, Timisoara, Romania, pp. 236–247 (2006)

    Google Scholar 

  34. Kovács, L., Kulcsár, B., Bokor, J., Benyó, Z.: LPV Fault Detection of Glucose-Insulin System. In: Proceedings of the 14th Mediterranean Conference on Control and Automation, Ancona, Italy, Electronic Publication TLA2-4 (2006)

    Google Scholar 

  35. Zhou, K.: Robust and Optimal Control. Prentice Hall, New Jersey (1996)

    MATH  Google Scholar 

  36. Helton, J.W., Merino, O.: Classical Control Using H ∞  Methods: Theory, Optimization and Design. SIAM, Philadelphia (1998)

    Google Scholar 

  37. Kovács, L., Paláncz, B., Benyó, B., Török, L., Benyó, Z.: Robust Blood-Glucose Control using Mathematica. In: Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, New York, USA, pp. 451–454 (2006)

    Google Scholar 

  38. Paláncz, B., Kovács, L., Benyó, B., Benyó, Z.: Robust Blood-Glucose Control of Type I Diabetes Patients under Intensive Care using Mathematica. In: Encyclopaedia of Healthcare Information Systems, Publ. Medical Information Science Reference, pp. 1210–1219 (2008)

    Google Scholar 

  39. Kovács, L., Kulcsár, B., Benyó, B., Benyó, Z.: Induced L2-norm Minimization of Glucose-Insulin System for Type I Diabetic Patients. In: Proceedings of the 7th IFAC Symposium on Modeling and Control in Biomedical Systems Including Biological Systems, Aalborg, Denmark, pp. 55–60 (2009)

    Google Scholar 

  40. Kovács, L., Paláncz, B., Borbély, E., Benyó, Z., Benyó, B.: Robust Control Techniques and its Graphical Representation in case of Type I Diabetes using Mathematica. In: Proceedings of the 8th International Symposium on Applied Machine Intelligence and Informatics, Herlany, Slovakia, pp. 71–75 (2010)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Control Engineering and Information Technology, Budapest University of Technology and Economics, H-1117, Budapest, Magyar tudósok krt. 2, Hungary

    Levente Kovács, Zoltán Benyó & Balázs Benyó

  2. Dept. of Mathematics, University “Politehnica” of Timisoara, RO-300006, Timişoara Romania, P-ta Victoriei Nr. 2

    Adalbert Kovács

Authors
  1. Levente Kovács
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  2. Zoltán Benyó
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  3. Adalbert Kovács
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  4. Balázs Benyó
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Editor information

Editors and Affiliations

  1. Óbuda University, Bécsi út 96/B, H-1034, Budapest, Hungary

    Imre J. Rudas  & János Fodor  & 

  2. Systems Research Institute, Polish Academy of Sciences, Ul.Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

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Kovács, L., Benyó, Z., Kovács, A., Benyó, B. (2010). New Principles and Adequate Robust Control Methods for Artificial Pancreas. In: Rudas, I.J., Fodor, J., Kacprzyk, J. (eds) Computational Intelligence in Engineering. Studies in Computational Intelligence, vol 313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15220-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-15220-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15219-1

  • Online ISBN: 978-3-642-15220-7

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