Skip to main content
Log in

Robust and self-tuning blood flow control during extracorporeal circulation in the presence of system parameter uncertainties

  • Published:
Medical and Biological Engineering and Computing Aims and scope Submit manuscript

Abstract

Three different discrete controllers were designed and tuned to be used in conjunction with a rotary blood pump during cardiopulmonary heart-lung support. The controllers were designed to operate in both steady and pulsatile modes. The system and methods were tested in a circulatory haemodynamic simulator. To guarantee stable control of the non-linear circulatory system in the presence of patient parameter uncertainties, a proportional plus integral (PI) and an H controller were robustly tuned, using a non-linear time-varying model. (H refers to the Hardy space, the set of bounded functions, analytic in the right half plane. The H controler is the solution to the H norm optimisation problem.) A self-tuning general predictive controller (GPC), together with an adaptive Kalman filter (KF) estimator, was compared with the two robustly tuned controllers. The closed-loop blood flow control circuit was set up in simulation routines first. The blood flow controllers were validated in a circulatory hydrodynamic simulator (MOCK) combined with a rotary blood pump. Parameters of the system simulator were changed continuously, and the controllers were tested over a wide range of different operating points. Disturbances in the form of discontinuous additive parameter uncertainties were applied. The closed-loop systems remained robustly stable. The robustly tuned H controller showed the best control performance, in contrast to the GPC controller, which was near instability in regions of strongly varying non-linear system gain. Compared with the H controller, the PI controller showed slightly worse behaviour, but the closed-loop response was acceptable, even in regions of strongly varying non-linear system gain and during pulsatile perfusion. The rotary blood pump could provide stationary and pulsatile perfusion under control conditions. Controlled variables were hereby mean blood flow, pulsatility index and heart rate. All three controllers were developed for an arterial mean flow of 0–6 l min−1 and a heart rate of up to 70 beats per minute. Pulsatile closed-loop perfusion could provide up to 30 mmHg pressure variation in the simulated ascending aorta at a mean flow of 3l min−1.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Anbe, J., Nakajima, H., Ogura, Y., Ozeki, M., Mitsuishi, T., Akasaka, T., andTobi, T. (1992a): ‘Development of a computerregulated extracorporeal circulation system’,Artif. Organs Today,2, pp. 117–125

    Google Scholar 

  • Anbe, J., Tobi, T., Nakajima, H., Akasaka, T. and OKINAGA, K. (1992b): ‘Microcomputer-based automatic regulation of extracorporeal circulation: a trial for the application of fuzzy inference’,Artif. Organs,16, pp. 532–538

    Google Scholar 

  • Avanzolini, G., Barbini, P., Capello, A., andCevenini, G. (1988): ‘Cades simulation of the closed-loop cardiovascular system’,Int. J. Biomed. Comput.,22, pp. 39–49

    Article  Google Scholar 

  • Avolio, A. P. (1980): ‘Multi-branched model of the human arterial system’,Med. Biol. Eng. Comput.,18, pp. 709–718

    Google Scholar 

  • Bauernschmitt, R., Naujokat, E., Mehmanesh, H., Schulz, S., Vahl, C. F., Hagl, S., andLange, R. (1999): ‘Mathematical modelling of extracorporeal circulation: simulation of different perfusion regimens’Perfusion,14, pp. 321–330

    Google Scholar 

  • Beppu, T., Imai, Y., andFukui, Y. (1992): ‘Computer-controlled cardiopulmonary bypass system’,Syst. Comput. Jpn.,23, pp. 74–84

    Google Scholar 

  • Beppu, T., Imai, Y., andFukui, Y. (1995): ‘A computerized control system for cardiopulmonary bypass’,J. Thorac. Cardiovasc. Surg.,109, pp. 428–438

    Google Scholar 

  • Boschetti, F., Montevecchi, F. M., andFumero, R. (1997): ‘Virtual extracorporeal circulation process’,Int. J. Artif. Organs,20, pp. 341–351

    Google Scholar 

  • Clarke, D. W., Mohtadi, C., andTuffs, P. S. (1987): ‘Generalized predictive control-Part I/II’,Automatica,23, pp. 137–140

    Google Scholar 

  • De Pater, L. (1966): ‘An electrical analogue of the human circulatory system’,PhD thesis, University of Groningen

  • Frank, O. (1899): ‘Die Grundform des arteriellen Pulses’,Z. Biol.,37, pp. 483–526

    Google Scholar 

  • Fukui, Y., Tsuchiya, K., andImai, Y. (1982): ‘Computer controlled extracorporeal circulation (ECC) with pulsatile perfusion for an infant’,Trans. Am. Soc. Artifn. Intern. Organs,28, pp. 133–137

    Google Scholar 

  • Göbel, C., Arvand, A., Eilers, R., Marselle, O., Bals, C., Meyns, B., Flameng, W., Rau, G., andReul, H. (2001): ‘Development of the MEDOS/HIA DeltaStream extracorporeal rotary blood pump’,Artif. Organs,25, pp. 358–365

    Google Scholar 

  • Gourlay, T., andTaylor, K.M. (1994): ‘Pulsatile flow and membrane oxygenators’,Perfusion,9, pp. 189–196

    Google Scholar 

  • Gundel, W., Cherry, G., Rajagopalan, B., Tan, L.-B., Lee, G., andSchultz, D. (1981): ‘Aortic input impedance in man: acute response to vasodilator drugs’,Circulation,63, pp. 1305–1314

    Google Scholar 

  • Hettrick, D. A., Pagel, P.S., andWarltier, D. C. (1995): ‘Differential effects of isoflurane and halothane on aortic input impedance quantified using a three-element Windkessel model’,Anesthesiology,83, pp. 361–373

    Google Scholar 

  • Kalman, R. E. (1960): ‘A new approach to linear filtering and prediction problems’,Trans. ASME J. Basic Eng.,82, pp. 35–45

    Google Scholar 

  • Kay, P. H., andMunsch, C. M. (2004): ‘Techniques in extracorporeal circulation’, (Arnold, London, U.K., 2004)

    Google Scholar 

  • Latson, T. W., Hunter, W. C., Katoh, N., andSagawa, K. (1988): ‘Effect of nitroglycerin on aortic impedance, diameter, and pulsewave velocity’,Circ. Res.,62, pp. 884–890

    Google Scholar 

  • Lowe, D., Hettrick, D. A., Pagel, P. S., andWarltier, D. C. (1996): ‘Propofol alters left ventricular afterload as evaluated by aortic input impedance in dogs’,Anesthesiology,84, pp. 368–376

    Google Scholar 

  • Lunze, J. (2002): ‘Regelungstechnik 2’, (Springer-Verlag, Berlin, Germany, 2002)

    Google Scholar 

  • McInnis, B., Guo, Z-W., Lu, P., andWang, J.-C. (1985): ‘Adaptive control of left ventricular bypass assist devices’,IEEE Trans. Automat. Contr.,30, pp. 322–329

    Article  Google Scholar 

  • Nagel, M. (2004): ‘Aufbau eines Versuchsstandes zur Simulation des menschlichen Kreislaufs unter den Bedingungen der extrakorporalen membranoxygenation (ECMO)’.Master Thesis, Dortmund University

  • Nelles, O. (2001): ‘Nonlinear system identification’, (Springer-Verlag, Berlin, Germany, 2001)

    Google Scholar 

  • Nishida, H., Beppu, T., Nakajima, M., Nishinaka, T., Nakatani, H., Ihashi, K., Katsumata, T., Kitamura, M., Aomi, S., Endo, M.,et al. (1995): ‘Development of an autoflow cruise control system for a centrifugal pump’,Artif. Organs,19, pp. 713–718

    Google Scholar 

  • Ogata, K. (1987): ‘Discrete —time control systems’ (Prentice — Hall, New Jersey, USA, 1987)

    Google Scholar 

  • Pennati, G., Fiore, G. B., Laganá, K., andFumero, R. (2004): ‘Mathematical modelling of fluid dynamics in pulsatile cardiopulmonary bypass’,Artif. Organs,28, pp. 196–209

    Article  Google Scholar 

  • Pepine, C. J., Nichols, W. W., Curry, R. C., andConti, C. R. (1979): ‘Aortic input impedance during nitroprusside infusion. A reconsideration of afterload reduction and beneficial action’,J. Clin. Invest.,64, pp. 643–654

    Google Scholar 

  • Reul, H., Minamitani, H., andRunge, J (1975): ‘A hydraulic analog of the systemic and pulmonary circulation for testing artificial hearts’,Proc. ESAO,2, pp. 120–127

    Google Scholar 

  • Rideout, V. C. (1972): ‘Cardiovascular system simulation in biomedical engineering education’,IEEE Trans. Biomed. Eng.,19, pp. 101–107

    Google Scholar 

  • Schwarzhaupt, A., andKiencke, U. (1998): ‘Entwicklungen in der Automatisierung von Herz-Lungen-Maschinen’,Automatisierung-stechnische Praxis,40, pp. 21–24

    Google Scholar 

  • Schwarzhaupt, A., Qaqunda, B., andKiencke, U. (1998): ‘Entwurf eines prädiktiven MIMO-Reglers für Herz-Lungen-Maschinen auf der Grundlage eines Modells der extrakorporalen Zirkulation’,Biomed. Tech.,43, pp. 336–337

    Google Scholar 

  • Schima, H., Honigschnabel, J., Trubel, W., andThoma, H. (1990): ‘Computer simulation of the circulatory system during support with a rotary blood pump’,ASAIO Trans.,36, pp. 252–254

    Google Scholar 

  • Segers, P., Dubois, F., De Wachter, D., andVerdonck, P. (1998): ‘Role and Relevancy of a Cardiovascular Simulator’,CVE.,3, pp. 48–56

    Google Scholar 

  • Shimooka, T., Mitamura, Y., andYuhta, T. (1991): ‘Investigation of parameter estimator and adaptive controller for assist pump by computer simulation’,Artif. Organs,15, pp.119–128

    Google Scholar 

  • Snyder, M. F., Rideout, V. C., andHillestad, R. J. (1968): ‘Computer modelling of the human systemic arterial tree’,J. Biomech.,1, pp. 341–353

    Article  Google Scholar 

  • Soejima, K., Nagase, Y., Ishihara, K., Takanashi, Y., Imai, Y., Tsuchiya, K., andFukui, Y. (1983): ‘Computer-assisted automatic cardiopulmonary bypass system for infants’, inAtsumi, K., Maekawa, M., andOta, K. (Eds). ‘Progress in artificial organs’ (ISAO Press, Cleveland, OH, USA, 1983), pp. 918–922

    Google Scholar 

  • Womersley, J. R. (1957): ‘An elastic tube theory of pulse transmission and oscillatory flow in mammalian arteries’.WADC Technical Report, pp. 56–614

  • Wright, G. (1988): ‘The hydraulic power outputs of pulsatile and nonpulsatile cardiopulmonary bypass pumps’,Perfusion,3, pp. 251–262

    Google Scholar 

  • Yih-Choung, Y., Boston, J. R., Simaan, M. A., andAntaki, J. F. (1998): ‘Estimation of systemic vascular bed parameters for artificial heart control’,IEEE Trans. Automat. Control. 43, pp. 765–778

    Google Scholar 

  • Zames, G. (1981): ‘Feedback and optimum sensitivity: Model reference transformations, multiplicative seminorms, and approximate inverses’,IEEE Trans. Automat. Control,26, pp. 301–320

    Article  MATH  MathSciNet  Google Scholar 

  • Zames, G., andFrancis, B. (1983): ‘Feedback, minimax sensitivity, and optimum robustness’,IEEE Trans. Autom. Control,28, pp. 585–601

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to B. J. E. Misgeld.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Misgeld, B.J.E., Werner, J. & Hexamer, M. Robust and self-tuning blood flow control during extracorporeal circulation in the presence of system parameter uncertainties. Med. Biol. Eng. Comput. 43, 589–598 (2005). https://doi.org/10.1007/BF02351032

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02351032

Keywords

Navigation