摘要
目的缺氧是人类进入高原生活和工作面临的最严峻的挑战之一,因此需要适量的低氧训练以减轻因缺氧引发的高原反应。本文设计了一种新型常压低氧舱模型的控制系统,使舱内氧浓度能够模拟不同海拔高度高原的氧浓度,用于低氧训练和低氧研究。方法控制系统采用模糊自适应算法,该算法结合专家算法与PD算法,能进行参数自我调整以适应环境的大时滞性和不稳定性。结果经过12 d低氧训练的检验,该控制系统使舱内海拔高度维持在目标范围以内,舱内环境在出现干扰后能及时恢复稳定。结论该控制系统能克服低氧舱复杂多变的环境特性,鲁棒性强,精度较高,为长时间的低氧训练和低氧实验提供了重要平台。
Objective Hypoxia is one of the greatest threatens to those who come to plateau for living and working, therefore a proper amount of hypoxic training is essential for them to reduce altitude sickness caused by hypoxia before going there. This paper designs a control system for a new hypoxic chamber, which can simulate the oxygen concentration on plateau of different altitudes for hypoxic trainings and experiments. Methods The control system is based on fuzzy self-learning algorithm combined with expert algorithm and PD algorithm, with the ability to justify parameters itself to fit the environment of time-delay and instability. Results During a 12-day-test of hypoxic training, the simulating ahitudes inside the chamber are controlled within expected limits, which is able to recover after interference occurred. Conclusions This system solves the problem of controlling difficulty due to the complex environment of the chamber, and provides strong robustness as well as high accuracy, which supplies a significant platform for hypoxic trainings and experiments.
出处
《北京生物医学工程》
2014年第4期397-402,共6页
Beijing Biomedical Engineering
关键词
常压低氧舱
大时滞系统
模糊自适应
normal haric hypoxic chamber
large time-delay system
fuzzy self-adaption
