Multi-drug Infusion Control Using Model Reference Adaptive Algorithm

  • S. Enbiya
  • M. A. Hossain
  • F. Mahieddine
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 93)


Control of physiological states such as mean arterial pressure (MAP) has been successfully achieved using single drug by different control algorithms. Multi-drug delivery demonstrates a significantly challenging task as compared to control with a single-drug. Also the patient’s sensitivity to the drugs varies from patient to patient. Therefore, the implementation of adaptive controller is very essential to improve the patient care in order to reduce the workload of healthcare staff and costs. This paper presents the design and implementation of the model reference adaptive controller (MRAC) to regulate mean arterial pressure and cardiac output by administering vasoactive and inotropic drugs that are sodium nitroprusside (SNP) and dopamine (DPM) respectively. The proposed adaptive control model has been implemented, tested and verified to demonstrate its merits and capabilities as compared to the existing research work.


Mean Arterial Pressure Blood Pressure Control Sodium Nitroprusside Internal Model Control Model Reference Adaptive Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ang, P.C.A., Ang, B.W., Zhu, K.Y.: A Cardiovascular Model for Blood Pressure Control Systems. In: ICBPE, pp. 1–8 (2009)Google Scholar
  2. 2.
    Furutani, E., Araki, M., Kan, S., et al.: An Automatic Control System of the Blood Pressure of Patients under Surgical Operation. International Journal Control, Automation, and Systems 2, 39–54 (2004)Google Scholar
  3. 3.
    Zheng, H., Zhu, K.: Automated Postoperative Blood Pressure Control. Journal of Control Theory and Applications 3, 207–212 (2005)zbMATHCrossRefGoogle Scholar
  4. 4.
    Slate, J.B., Sheppard, L.C.: Automatic Control of Blood Pressure by Drug Infusion. IEE Proc. 129, 639–645 (1982)Google Scholar
  5. 5.
    Zhu, K.Y., Zheng, H., Zhaug, D.G.: A Computerized Drug Delivery Control System for Regulation of Blood Pressure. IC-MED 2, 1–13 (2008)Google Scholar
  6. 6.
    Behbehain, K., Cross, R.R.: A Controller for Regulation of Mean Arterial Blood Pressure Using Optimum Nitroprusside Infusion Rate. IEEE Trans. On Biomed. Eng. 38, 513–521 (1991)CrossRefGoogle Scholar
  7. 7.
    Poterlowicz, K., Hossain, M.A., Majumder, M.A.A.: Optimal IMC System for Blood Pressure Control. In: IEEE Proceeding of CS 2007, pp. 113–117 (2007)Google Scholar
  8. 8.
    Enbiya, S., Hossain, A., Mahieddine, F.: Performance of Optimal IMC and PID Controllers for Blood Pressure Control. In: IFMBE Proceedings, vol. 24, pp. 89–94 (2009)Google Scholar
  9. 9.
    Yu, C., Roy, R.J., Kaufman, H.: A Circulatory Model for Combined Nitroprusside-Dopamine Therapy in Acute Heart Failure. Med. Prog. Tech. 16, 77–88 (1990)Google Scholar
  10. 10.
    Achuthan, G., Alekseyenko, Y., Ishihara, A., et al.: Indirect Adaptive Control of Drug Infusion For A Circulatory System Model. In: Proceedings of the 7th Mediterranean Conference on Control and Automation, pp. 1007–1016 (1999)Google Scholar
  11. 11.
    Voss, G.I., Katona, P.G., Chizeck, H.J.: Adaptive Multivariable Drug Delivery: Control of Arterial Pressure and Cardiac Output in Anesthetized Dogs. IEEE Trans. Biomed. Eng. BME-34, 617–623 (1987)CrossRefGoogle Scholar
  12. 12.
    Yu, C., Roy, R.J., Kaufman, H., et al.: Multiple-Model Adaptive Predictive Control of Mean Arterial Pressure and Cardiac Output. IEEE Trans. Biomed. Eng. 39, 765–778 (1992)CrossRefGoogle Scholar
  13. 13.
    Sheppard, L.C., Shotts, J.F., et al.: Computer Controlled Infusion of Vasoactive Drugs in Post Cardiac Surgical Patients. In: IEEE-EMBS Denver, October 6-7, pp. 280–284 (1979)Google Scholar
  14. 14.
    Koivo, A.J., Smollen, V.F., Barile, R.V.: An Automated Drug Administration System to Control Blood Pressure in Rabbits. Math. Biosc. 38, 45–56 (1978)CrossRefGoogle Scholar
  15. 15.
    Koivo, A.J.: Automatic Continuous-Time Blood Pressure Control in Dogs by Mean of Hypotensive Drug Injection. IEEE Trans. Biomed. Eng. BME-27, 574–581 (1980)CrossRefGoogle Scholar
  16. 16.
    Koivo, A.J.: Microprocessor-Based Controller for Pharmodynamical Applications. IEEE Trans. Auto. Control AC-26, 1208–1212 (1981)CrossRefGoogle Scholar
  17. 17.
    Stern, K.S., Walker, B.K., Katona, P.G.: Automated Blood Pressure Control Using a Self-Tuning Regulator. IEEE Frontiers Engin. Health Care, 255–258 (1981)Google Scholar
  18. 18.
    Kaufman, H., Roy, R.J., Xu, X.: Model Reference Adaptive Control of Drug Infusion Rate. Automatica 20, 205–209 (1984)zbMATHCrossRefGoogle Scholar
  19. 19.
    Barney, E.H., Kaufman, H.: Model Reference Adaptive Control of Cardiac Output and Blood Pressure through Two Drug Infusions. In: Proceedings of the 5th IEEE International Symposium on Intelligent Control, vol. 2, pp. 739–744 (1990)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • S. Enbiya
    • 1
  • M. A. Hossain
    • 2
  • F. Mahieddine
    • 3
  1. 1.School of Computing, Informatics and MediaUniversity of BradfordBradfordUK
  2. 2.School of Computing, Engineering and Information SciencesNorthumbria UniversityUK
  3. 3.School of Engineering, Design and TechnologyUniversity of BradfordBradfordUK

Personalised recommendations