基于遗传算法的麻醉1型和区间2型模糊PID控制设计

Hugo Araujo, Bo Xiao, Chuang Liu, Yanbin Zhao, H. Lam
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引用次数: 18

摘要

本文介绍了通过控制异丙酚和瑞芬太尼两种药物的浓度靶点,自动给药来调节临床手术麻醉过程中双谱(BIS)指数。为实现自动给药,收集42例患者的真实临床数据,构建患者模型,包括药代动力学模型和药效学模型,描述患者对输入药物的动力学反应。将42例患者的模型取平均值,得到名义麻醉模型,用于设计控制方案。采用线性PID控制器、1型(T1)模糊PID控制器和区间2型(IT2)模糊PID控制器三种PID控制器,利用标称患者模型对BIS指标进行调节。通过最小化测量控制性能的代价函数,利用遗传算法获得PID增益和隶属函数。在不同的场景下测试训练最好的PID控制器,并比较其控制性能。仿真结果表明,IT2模糊PID控制器对BIS指标的控制效果最好,T1模糊PID控制器的控制效果次之。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of Type-1 and Interval Type-2 Fuzzy PID Control for Anesthesia Using Genetic Algorithms
This paper presents the automatic drug administration for the regulation of bispectral (BIS) index in the anesthesia process during the clinical surgery by controlling the concentration target of two drugs, namely, propofol and remifentanil. To realize the automatic drug administration, real clinical data are collected for 42 patients for the construction of patients’ models consisting of pharmacokinetic and pharmacodynamic models describing the dynamics reacting to the input drugs. A nominal anesthesia model is obtained by taking the average of 42 patients’ models for the design of control scheme. Three PID controllers are employed, namely linear PID controller, type-1 (T1) fuzzy PID controller and interval type-2 (IT2) fuzzy PID controller, to regulate the BIS index using the nominal patient’s model. The PID gains and membership functions are obtained using genetic algorithm (GA) by minimizing a cost function measuring the control performance. The best trained PID controllers are tested under different scenarios and compared in terms of control performance. Simulation results show that the IT2 fuzzy PID controller offers the best control strategy regulating the BIS index while the T1 fuzzy PID controller comes the second.
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