基于模型预测控制的低温控温策略设计及实验验证

Design and experimental verification of cryogenic temperature-control strategy based on model predictive control

低温温度计的标定中,控温策略是低温温度计标定效率和精度的重要影响因素。本研究搭建了以液氦为冷源的低温温度计全自动标定系统,通过温控仪和Python/QT编写了上位机控制程序,对标定过程中所遇到的控温性能问题进行研究。提出一种基于模型预测控制和PID结合的控温策略,通过计算机仿真进行参数优化与实验测试的方法,对PID控温和模型预测控制控温进行实验验证。结果表明,采用模型预测控制后,温度超调量仅为PID模式下的45.42%,稳态调节时间缩短为PID下的23.61%。该控制方法能够显著提高低温系统的控温性能。

For the calibration of cryogenic thermometers,the temperature control strategy is an important influencing factor for the calibration efficiency and accuracy of cryogenic thermometers.In this research,a fully automatic calibration system for cry⁃ogenic thermometer with liquid helium as the cold source was built,and a host computer control program was written based on the temperature controller and Python/QT to analyze the temperature control performance of different control algorithms in the calibra⁃tion process.In this paper,a temperature control strategy based on the combination of model predictive control and PID was pro⁃posed,and the method of parameter optimization and experimental testing through computer simulation was given,and the two temperature controls of PID and model predictive control were experimentally verified.The results show that after using the model predictive control,the temperature overshoot is only 45.42%in PID mode,and the steady-state adjustment time is shortened to 23.61%under PID.This control method can significantly improve the temperature control performance of cryogenic systems.