北京生物医学工程

一氧化氮流量控制系统仿真研究

Simulation research on nitric oxide flow control system

作者：黄科梁刘广清吴海啸胡燕海

单位：宁波大学机械工程与力学学院（浙江宁波315211）<br />宁波戴维医疗器械股份有限公司（浙江宁波 315712）<br />通信作者：胡燕海，教授。E-mail: huyanhai@nbu.edu.cn

分类号：R318.04

出版年·卷·期（页码）：2023·42·1（74-80）

摘要：

目的针对模糊规则难以人为整定的难题，开发一种基于改进遗传算法整定模糊规则的模糊比例-积分-微分（proportional-integral-derivative，PID）算法，并应用于一氧化氮流量控制系统。方法首先采用机理法结合阶跃响应法的形式进行控制对象建模，再运用MATLAB进行控制算法的设计，最后将该算法与通用规则模糊PID算法和位置式PID算法进行仿真对比。结果应用了该算法的一氧化氮流量控制系统具备超调小、几乎无稳态误差的特性，控制性能远远优于通用规则模糊PID算法和位置式PID算法。结论该算法可解决模糊规则难以人为整定的困难，改善模糊PID控制器控制性能，对提高NO流量控制精度、降低NO吸入疗法治疗风险具有参考价值。

Objective Aiming at the problem that fuzzy rules are difficult to set artificially, a fuzzy proportional-integral-derivative(PID) algorithm based on improved genetic algorithm to set fuzzy rules for NO flow control system is developed. Methods First of all, mechanism method combined with step response method was used for modeling of control object. Then, MATLAB was applied to design the control algorithm. At last, this algorithm was compared with fuzzy PID algorithm based on general rule and positional PID algorithm through simulation. Results The NO flow control system applying this algorithm had the characteristics of small overshoot and almost no steady-state error, and its control performance was far better than fuzzy PID algorithm based on general rule and positional PID algorithm. Conclusions This algorithm which can solve the difficulty of artificial adjustment of fuzzy rules and improve control performance of fuzzy PID controller has reference value for improving the accuracy of NO flow control and reducing the treatment risk of inhaled NO therapy.

参考文献：

[1] 张梦莹, 刘汉楚. 外源性一氧化氮吸入治疗新生儿持续性肺动脉高压研究进展[J]. 江汉大学学报（自然科学版）, 2018, 46(6) : 533-537.
Zhang MY, Liu HC. Research progress of exogenous nitric oxide inhalation on treatment of
persistent pulmonary hypertension of new-born[J]. Journal of Jianghan University（ Natural Science Edition）, 2018, 46(6) : 533-537.
[2] 刘学丹, 李晓春. 吸入一氧化氮治疗新生儿肺动脉高压的临床进展[J]. 安徽医学, 2014, 35(11) : 1618-1620.
[3] Teng RJ, Wu TJ. Persistent pulmonary hypertension of the newborn[J]. Journal of the Formosan Medical Association, 2013, 112 : 177-184.
[4] 伊洋, 贺仁忠. 吸入一氧化氮治疗呼吸衰竭的进展[J]. 医学综述, 2018, 24(5) : 966-971.
Yi Y, He RZ. Progress in the treatment of respiratory failure by inhaling nitric oxide[J]. Medical Recapitulate, 2018, 24(5) : 966-971.
[5] 王晓蕾, 孙海滨, 郁敏. 新生儿持续肺动脉高压治疗进展[J]. 医学综述, 2011, 17(21) : 3281-3283.?
Wang XL, Sun HB, Yu M. Advances in management of persistent pulmonary hypertension of the newborn[J]. Medical Recapitulate, 2011, 17(21) : 3281-3283.?
[6] 孙珵琭, 胡兆燕, 陈正龙. 一氧化氮治疗仪及其应用进展[J]. 北京生物医学工程, 2015, 34(6) : 649-656.
Sun CL, Hu ZY, Cheng ZL. Research progress in inhaled nitric oxide system[J]. Beijing Biomedical Engineering, 2015, 34(6) : 649-656.
[7] 郭秀荣, 杨季彪. 气体流量控制技术的研究现状[J]. 林业机械与木工设备, 2021, 49(1) : 4-7.
Guo XR, Yang JB. Research status of gas flow control technology[J]. Forestry Machinery & woodworking Equipment, 2021, 49(1) : 4-7.
[8] 高慧中, 路骏, 马小录. 基于增量式PID算法的气体流量控制方法[J]. 鱼雷技术, 2016, 24(2) : 132-136.
Gao HZ, Lu J, Ma XL. Incremental PID algorithm based gas flow control method[J]. Torpedo Technology, 2016, 24(2) : 132-136.
[9] 王春晨. 细胞培养气体混合控制系统研究[D]. 北京:军事科学院, 2018.
Wang CC. Research on the control system of gas mixture for cell culture[D]. Beijing : Academy of Military Sciences, 2018.
[10] 刘景康, 龙飞, 赵坤. 基于模糊PID的呼吸机流量控制系统的设计与实现[J]. 电子设计工程, 2019, 27(2) : 94-99.
Liu JK, Long F, Zhao K. Design and implement of flow control system for ventilator based on fuzzy PID[J]. Electronic Design Engineering, 2019, 27(2) : 94-99.
[11] 侯媛彬. 系统辨识[M]. 西安:西安电子科技大学出版社, 2014.
[12] 赵越, 孙立军, 吴瑕. 多变量解耦自抗扰控制在气体流量装置中的应用[J]. 化工学报, 2017, 68(9) : 3482-3493.
Zhao Y, Sun LJ, Wu X. Active disturbance rejection control on gas flow equipment by multivariable decoupling algorithm[J]. CIESC Journal, 2017, 68(9) : 3482-3493.
[13] 朱远帆, 杨海仕, 吴文阳. 基于前馈解耦的婴儿培养箱温湿度控制系统[J]. 北京生物医学工程, 2019, 38(3) : 246-250.
Zhu YF, Yang HS, Wu WY. Temperature and humidity control system of infant incubator based on feedforward decoupling[J]. Beijing Biomedical Engineering, 2019, 38(3) : 246-250.
[14] 金爱国, 杨海仕, 吴海啸. 基于P-变论域模糊自适应PID的婴儿辐射保暖台温控系统研究[J]. 宁波大学学报（理工版）, 2019, 32(1) : 52-56.
Jin AG，Yang HS，Wu HX.Study on temperature control system of infant radiant warmer based on proportion-variable universe fuzzy adaptive PID[J]. Journal of Ningbo University(Natural Science & Engineering Edition), 2019, 32(1) : 52-56.
[15] 郭亦文, 李军, 耿林宵. 基于遗传算法获取模糊规则[J]. 计算机应用, 2014, 34(10) : 2989-2993.
Guo YW, Li J, Geng LX. Fuzzy rule extraction based on genetic algorithm[J]. Journal of Computer Applications, 2014, 34(10) : 2989-2993.
[16] 李岩, 袁弘宇, 于佳乔. 遗传算法在优化问题中的应用综述[J]. 山东工业技术, 2019, 12 : 242-243.

服务与反馈：

【文章下载】【加入收藏】

提示：您还未登录，请登录！点此登录