基于改进遗传算法的气体混合控制系统的设计与仿真

摘要

针对传统气体混合存在精度低、混合时间长等问题,研究了以质量流量控制器为主的气体混合系统,设计了改进遗传算法整定PID参数的控制系统.利用模式识别建立了系统数学模型,针对标准遗传算法的缺陷,设计了一种改进比例选择算子并提出自适应法调整交叉、变异概率.进行仿真实验验证改进遗传算法优化PID控制系统的控制性能.实验结果表明,相比标准遗传算法和Z-N法优化PID,基于改进遗传算法优化PID控制系统具有更高的控制精度以及更快的混合时间.%A gas mixture system based on mass flow controller is developed and a control system based on PID optimized by IGA (improved genetic algorithm) is designed to solve the problem of low precision and long settling time of the traditional gas mixture.Firstly, the mathematical model of the gas mixture system is established through system identification.Secondly, an IGA based on an improved proportion selection operator and an adaptive crossover and mutation probability is proposed to overcome SGA's (standard genetic algorithm's) deficiency.Finally, simulation experiments are developed to verify the control effect of the IGA tuning of PID.The simulation experimental results show that the IGA tuning of PID has higher precision and quicker adjustment than the SGA and the Z-N tuning of PID.