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基于强化学习的化学发光免疫分析仪温度控制策略研究

李中伟 乔美英 王聪

科技创新与应用2024,Vol.14Issue(13):39-43,5.
科技创新与应用2024,Vol.14Issue(13):39-43,5.DOI:10.19981/j.CN23-1581/G3.2024.13.010

基于强化学习的化学发光免疫分析仪温度控制策略研究

李中伟 1乔美英 2王聪3

作者信息

  • 1. 河南理工大学 电气工程与自动化学院,河南 焦作 454003||安图实验仪器(郑州)有限公司,郑州 450016
  • 2. 河南理工大学 电气工程与自动化学院,河南 焦作 454003
  • 3. 安图实验仪器(郑州)有限公司,郑州 450016
  • 折叠

摘要

Abstract

Traditional PID control,as the most commonly used control algorithm,has a wide range of applications in the temperature control unit of fully automatic chemiluminescence immunoassay analyzer.However,there are problems such as difficulty in tuning PID control parameters,long adjustment time,and large overshoot.How to shorten temperature adjustment time,reduce overshoot,and further improve instrument inspection efficiency while ensuring temperature control accuracy has become a problem that needs to be solved,To address this issue,a temperature control algorithm based on Deep Deterministic Policy Gradient(DDPG)is applied,which can avoid relying on manual experience for PID parameter tuning,shorten temperature adjustment time,and significantly reduce overshoot.By analyzing the parameter indicators of temperature control through simulation experiments,the results show that this algorithm is superior to traditional PID control and fuzzy PID control algorithms,In terms of adjustment time,it has increased by 14.9%and 6.3%respectively,and in terms of overshoot,it has increased by 99.8%and 99.2%respectively,which is of great significance for improving the performance of the instrument.

关键词

发光免疫分析仪/温度控制/PID/DDPG/强化学习

Key words

luminescent immunoassay analyzer/temperature control/PID/DDPG/reinforcement learning

分类

信息技术与安全科学

引用本文复制引用

李中伟,乔美英,王聪..基于强化学习的化学发光免疫分析仪温度控制策略研究[J].科技创新与应用,2024,14(13):39-43,5.

科技创新与应用

2095-2945

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