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    Optimized PID control of depth of hypnosis in anesthesia

    251762.pdf (6.157Mb)
    Access Status
    Open access
    Authors
    Padula, Fabrizio
    Ionescu, C.
    Latronico, N.
    Paltenghi, M.
    Visioli, A.
    Vivacqua, G.
    Date
    2017
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Padula, F. and Ionescu, C. and Latronico, N. and Paltenghi, M. and Visioli, A. and Vivacqua, G. 2017. Optimized PID control of depth of hypnosis in anesthesia. Computer Methods and Programs in Biomedicine. 144: pp. 21-35.
    Source Title
    Computer Methods and Programs in Biomedicine
    DOI
    10.1016/j.cmpb.2017.03.013
    ISSN
    0169-2607
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/52922
    Collection
    • Curtin Research Publications
    Abstract

    Background and Objective: This paper addresses the use of proportional-integral-derivative controllers for regulating the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. In fact, introducing an automatic control system might provide significant benefits for the patient in reducing the risk for under- and over-dosing. Methods: In this study, the controller parameters are obtained through genetic algorithms by solving a min-max optimization problem. A set of 12 patient models representative of a large population variance is used to test controller robustness. The worst-case performance in the considered population is minimized considering two different scenarios: the induction case and the maintenance case. Results: Our results indicate that including a gain scheduling strategy enables optimal performance for induction and maintenance phases, separately. Using a single tuning to address both tasks may results in a loss of performance up to 102% in the induction phase and up to 31% in the maintenance phase. Further on, it is shown that a suitably designed low-pass filter on the controller output can handle the trade-off between the performance and the noise effect in the control variable. Conclusions: Optimally tuned PID controllers provide a fast induction time with an acceptable overshoot and a satisfactory disturbance rejection performance during maintenance. These features make them a very good tool for comparison when other control algorithms are developed.

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