麻醉中催眠成分的多参数模型预测控制与状态估计

2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) Pub Date : 2016-05-19 DOI:10.1109/AQTR.2016.7501357

I. Nascu, E. Pistikopoulos

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引用次数: 2

摘要

本文介绍了用于麻醉深度控制的多参数模型预测控制策略。基于包含药代动力学和药效学部分的详细室室模型，采用了两种不同的控制策略:标称多参数模型预测控制和多参数运动水平估计和模型预测控制。对12例处于诱导和维持阶段的患者进行了控制策略测试，并进行了对比分析。此外，还详细分析了患者之间和患者内部的变异性。仿真结果表明，该系统具有良好的性能和令人满意的性能。

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Multiparametric model predictive control and state estimation of the hypnotic component in anesthesia

This paper describes multiparametric model predictive control strategies for the control of depth of anaesthesia. Based on a detailed compartmental model featuring a pharmacokinetic and a pharmacodynamics part, two different control strategies are employed: a nominal multiparametric model predictive control and a simultaneous multiparametric moving horizon estimation and model predictive control. The control strategies are tested on a set of 12 patients in the induction and maintenance phase and analyzed comparatively. Moreover the inter-as well as the intra-patient variability is analyzed in detail. The performed simulations show good performances and satisfactory behavior.

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2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)

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