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[1] HUANG Keliang;LIU Guangqing;WU Haixiao;HU Yanhai(College of Mechanical Engineering and Mechanics,Ningbo University,Ningbo,Zhejiang Province 315211;Ningbo David Medical Device Co􀆰Ltd􀆰,Ningbo,Zhejiang Province 315712)

机构地区：[1]宁波大学机械工程与力学学院,浙江宁波315211 [2]宁波戴维医疗器械股份有限公司,浙江宁波315712

出　　处：《北京生物医学工程》2023年第1期74-80,共7页Beijing Biomedical Engineering

基　　金：国家自然科学基金(51705263);宁波市重大科技专项(2017C110030)资助。

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.

关 键 词：NO吸入疗法 阶跃响应法 改进遗传算法 模糊PID算法 气体流量控制 

分 类 号：R318.04[医药卫生—生物医学工程]