基于量子纠缠源系统的高精度数字温控仪PID算法的研究
Research on PID Algorithm of High Precision Digital Temperature Controller Based on Quantum Entanglement Source System
谢金 1王宁1
作者信息
- 1. 山西大学 物理电子工程学院,山西 太原 030006
- 折叠
摘要
量子纠缠在量子信息领域具有重要的意义,其中精准控制非线性晶体的温度是制备高品质量子纠缠的关键因素之一.为了提升量子纠缠源温控系统的智能化,本文研制开发了一种基于STM32F407Vex的数字温控仪,我们采用了遗传模糊免疫比例积分微分(Genetic Fuzzy Immune Proportional Integral Differential,GFI-PID)控制算法,它将比例积分微分(Proportional Integral Differential,PID)与模糊算法(Fuzzy Algorithm,FA)、免疫反馈机理、遗传算法(Genetic Algorithm,GA)相结合,可以在线整定PID参数,克服免疫参数选取不当而导致系统超调量大、响应速度过慢的问题.结果表明:相比于PID算法和模糊免疫PID(Fuzzy Immune Proportional Integral Differential,FI-PID)算法,采用该算法后,系统的超调量分别降低了6.8％和1.8％,上升时间分别降低了5％和3％,该方法降低了系统超调量,提高了系统的收敛速度和响应度,使温控仪具有较强的自整定功能和超前的自适应能力.
Abstract
Quantum entanglement plays an important role in the field of quantum information,among which precisely control-ling the temperature of nonlinear crystals is one of the most important factors in the preparation of high-quality quantum entangle-ment.In order to improve the intellectualization of temperature control system of quantum entanglement source,a digital tempera-ture controller based on STM32F407Vex is developed in this paper.We adopt the genetic fuzzy immune proportional integral differ-ential(GFI-PID)control algorithm,which combines PID with fuzzy algorithm(FA),immune feedback mechanism and genetic algo-rithm(GA).The PID parameters can be set online to overcome the problems of large overshoot and slow response caused by improp-er selection of immune parameters.The results show that:compared with PID algorithm and fuzzy Immune PID(FI-PID)algorithm,the overshoot of the system is reduced by 6.8％and 1.8％,and the rise time is reduced by 5％and 3％,respectively.This method re-duces the overshoot of the system and improves the convergence speed and responsiveness of the system,letting the temperature controller has strong self-tuning function and advanced self-adaptation ability.
关键词
量子纠缠源系统/非线性光学晶体/数字温控仪/遗传模糊免疫PID算法Key words
entangled source system/nonlinear crystal temperature control/digital temperature controller/genetic fuzzy immune PID algorithm引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据