基于粒子群算法的红外探测制冷系统

在红外探测制冷系统中,为了提高控制参数的准确性,采用粒子群优化算法,对传统Z-N算法得到的参数进行优化.优化过程包括适应度函数选择、参数编码以及参数提取.根据粒子群算法提取的PID控制参数,通过TEC制冷控制测试台控制红外光子探头工作.结果表明,优化后的算法能准确地控制红外探头工作在设定的温度,减少了系统的零点漂移,提高了制冷系统的稳定性.

Infrared Detection Refrigeration System Based on Particle Swarm Optimization Algorithm

In the infrared detection refrigeration systems,in order to improve the accuracy of the control parameters,using particle swarm optimization(PSO) algorithm to optimize the parameters of conventional Z-N method.Optimization process includes fitness function selection,parameter encoding and parameter extraction.According to the extraction of PSO algorithm for PID control parameters,the TEC refrigeration control test bench controls infrared photon probe.The results show that the optimized algorthm can accurately control the infrared sensor in the set temperature,which can reduce zero drift of the system,and improve the stability of the refrigeration system.