基于BSO算法的SiO2沉积速率控制

SiO2Deposition Rate Control Based on Beetle Swarm Optimization Algorithm

为了提高SiO2薄膜质量,将晶振膜厚控制仪用于沉积速率采集,采用闭环反馈控制电子枪灯丝两端电压,利用Ziegler-Nichols整定经验法确定PID参数范围,并通过天牛须搜索-粒子群算法(BSO)实现参数自整定,从而改变电子束束流大小,实现薄膜沉积速率的稳定控制;实验结果表明,在本控制系统下,沉积速率在4 s左右建立稳态且波形无明显振荡,相比于遗传算法,BSO算法全局搜索能力更强,该方法可用于电子束蒸发镀膜过程中不同靶材沉积速率的控制,可进一步提高薄膜表面均匀性。

In order to improve the quality of SiO2 thin films,the crystal diaphragm thickness controller was used to capture the deposition rate and for the acquisition of deposition rate. The Ziegler-Nichols tuning empirical method was used to determine the PID parameter range. The parameters were self-tuning by means of the lonnix whisker searcher particle swarm optimization(BSO)to change the electron beam beam size and realize the stable control of film deposition rate. Experimental results showed that under the control system,the deposition rate was stable around 4 s and the waveform did not oscillate significantly. Compared with the genetic algorithm,the BSO algorithm has a stronger global search ability. This method can be used to control the deposition rate of different targets in the process of electron beam evaporation and coating,and can further improve the surface uniformity of the film.