Modeling and control of pharmacodynamics

Beck, Carl

doi:10.1016/j.ejcon.2015.04.006

Cited by 35 publications

(25 citation statements)

References 81 publications

(107 reference statements)

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“…These models have been developed, tested, and validated on a wide range of real patient data and have often used in the literature for the control of anesthesia [60]. In this paper, we use the model presented in [58] given by An additional compartment, namely, the effect compartment, is introduced to represent the time delay between the observed effect and the plasma concentration.…”

Section: Pharmacokinetic/pharmacodynamic Modelmentioning

confidence: 99%

Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

Navarro-Guerrero

Tang

2018

Algorithms

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Abstract:The design of a fractional-order closed-loop model reference adaptive control (FOCMRAC) for anesthesia based on a fractional-order model (FOM) is proposed in the paper. This proposed model gets around many difficulties, namely, unknown parameters, lack of state measurement, inter and intra-patient variability, and variable time-delay, encountered in controller designs based on the PK/PD model commonly used for control of anesthesia, and allows to design a simple adaptive controller based on the Lyapunov analysis. Simulations illustrate the effectiveness and robustness of the proposed control.

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Section: Pharmacokinetic/pharmacodynamic Modelmentioning

confidence: 99%

Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

Navarro-Guerrero

Tang

2018

Algorithms

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“…1. The compartment model the brain and is related to the concentration in the central compartment through a first order dynamic (Beck (2015)). So, the compartmental model can be expressed as follows:…”

Section: The Traditional Patient Modelmentioning

confidence: 99%

Time-optimal control for the induction phase of anesthesia

et al. 2017

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This paper deals with the control of the induction phase of anesthesia. The objective during this first phase is to bring the patient from its awake state to a final state corresponding to some given depth of anesthesia, measured by the BIS (Bispectral index), within a minimum time. This optimal time control strategy is addressed by means of the maximum principle of Pontryagin. Furthermore, since the anesthesia model presents multiple time scale dynamics that can be split in two groups : fast and slow and since the BIS is a direct function of the fast ones, we only consider the optimal control of fast states. The final state of the slow dynamics is let free. The synthesis approach of the optimal control is detailed then tested in the case of a nominal patient.

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“…The sensitivity of the UV-curing process to inhibition by oxygen requires additional action. A step forward to overcome the oxygen inhibition has been taken recently with the curing of UV-painted three-dimensional objects under CO 2 -atmosphere [48]. In the property spectrum of UV coatings, there are different features that have to be balanced out with respect to being feasible for automotive-exterior build-on parts.…”

Section: Paint Materialsmentioning

confidence: 99%