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Related Experiment Videos

Evaluation of a long-range adaptive predictive controller for computerized drug delivery systems

K E Kwok1, S L Shah, A S Clanachan

  • 1Department of Chemical Engineering, University of British Columbia, Vancouver, Canada.

IEEE Transactions on Bio-Medical Engineering
|January 1, 1995
PubMed
Summary

This study introduces an adaptive control system for computerized drug delivery, effectively regulating mean arterial pressure using sodium nitroprusside. The system demonstrated precise control and robustness against disturbances.

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Area of Science:

  • Biomedical Engineering
  • Control Systems
  • Pharmacology

Background:

  • Computerized drug delivery systems require precise control for patient safety and therapeutic efficacy.
  • Adaptive control strategies are crucial for managing physiological variables like mean arterial pressure (MAP) in dynamic environments.

Purpose of the Study:

  • To develop and evaluate a closed-loop adaptive control system for computerized drug delivery.
  • To assess the system's ability to regulate mean arterial pressure (MAP) using sodium nitroprusside infusion.

Main Methods:

  • Implementation of a generalized predictive control law with a terminal matching condition for drug infusion.
  • Utilizing a control-relevant, long-range identification algorithm for on-line parameter estimation.
  • Experimental validation in mongrel dogs to evaluate setpoint tracking and disturbance rejection of MAP.

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Main Results:

  • The system achieved hypotension induction within an average of 2.44 +/- 0.31 minutes without MAP overshoots.
  • Mean arterial pressure remained within 5 mm Hg of the target 96.2% of the time under stable conditions.
  • The control system demonstrated robustness and effectiveness when subjected to unpredictable disturbances.

Conclusions:

  • The developed closed-loop adaptive control system is effective and robust for computerized drug delivery.
  • The system accurately regulates mean arterial pressure, even in the presence of physiological constraints and disturbances.
  • This approach offers a promising solution for automated and precise drug administration in clinical settings.